CN115610479B - Railway line state inspection system and method - Google Patents
Railway line state inspection system and method Download PDFInfo
- Publication number
- CN115610479B CN115610479B CN202211170733.0A CN202211170733A CN115610479B CN 115610479 B CN115610479 B CN 115610479B CN 202211170733 A CN202211170733 A CN 202211170733A CN 115610479 B CN115610479 B CN 115610479B
- Authority
- CN
- China
- Prior art keywords
- turnout
- image
- train
- track
- loop
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
Classifications
-
- 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 vehicle trains
- B61L23/04—Control, warning, or like safety means along the route or between vehicles or vehicle trains for monitoring the mechanical state of the route
Abstract
The invention discloses a railway line state inspection system and a method, wherein the system comprises the following steps: the speed detection module is arranged at the axle end of a wheel of the train or on a motor gear box and is used for detecting the speed of the train; the turnout detection module comprises a plurality of turnout cameras and is arranged at the bottom of a train and used for respectively acquiring an inside image and an outside image of a railway of the turnout at the railway turnout according to the speed of the train and prestored kilometer sign information; the image processing module is used for judging whether faults exist on the inner side and/or the outer side of the track of the turnout according to the acquired inner side image and outer side image of the track of the turnout and the pre-stored normal image and by adopting a pre-set deep learning target detection model. By the technical scheme provided by the invention, the inspection in an unattended mode can be realized, various defects of a detection line can be rapidly and correctly identified, the inspection is convenient, and decision basis can be provided for fault hidden danger early warning and scientifically making a maintenance plan.
Description
Technical Field
The invention relates to a railway line state inspection technology, in particular to a railway line state inspection system and a railway line state inspection method.
Background
At present, the inspection operation condition and the operation quality record of the turnout and the loop line mainly depend on manual work, the traceability of the mode is lower, the states of the turnout and the loop line are influenced by factors such as the outside, abrasion and the like, and various defects are easy to occur in a railway line. If defects of turnouts and loops cannot be found in time in the running process of the vehicle, serious potential safety hazards are likely to be caused. As for manual detection, the influence of the profession and omission of the inspection operators is likely to cause confusion of tracking information, so that the way of inspection operation is difficult to meet the requirement of increasingly enhanced railway line safety precaution management.
In summary, at present, inspection analysis and state conditions of turnout and loop line images are manually detected, and the current inspection mode occupies a lot of manpower and material resources, and meanwhile, the quality of manual detection cannot be guaranteed.
Disclosure of Invention
The invention aims to provide a railway line state inspection system and method, which are used for solving the problem that the manual inspection quality cannot be ensured in the prior art.
In order to achieve the above object, the present invention provides a railway line status inspection system, comprising: the speed detection module is arranged at the axle end of a wheel of the train or on a motor gear box and is used for detecting the speed of the train; the turnout detection module comprises a plurality of turnout cameras and is arranged at the bottom of a train and used for respectively acquiring an inside image and an outside image of a railway of the turnout at the railway turnout according to the speed and prestored kilometer sign information; and the image processing module is used for judging whether faults exist on the inner side and/or the outer side of the track of the turnout according to the acquired inner side image and outer side image of the track of the turnout and the pre-stored normal image and by adopting a pre-set deep learning target detection model.
Preferably, the railway line status inspection system further comprises: the loop detection module comprises a loop camera, is arranged at the bottom of the train and is used for acquiring loop images in real time; the image processing module is also used for judging whether the loop has defects according to the loop image acquired in real time and the pre-stored loop initial state.
Preferably, the switch detection module includes: the train position judging unit is used for judging the position of the train according to the speed and the kilometer post information so as to determine the time of the train reaching the turnout position; and the turnout image acquisition unit comprises a plurality of turnout cameras and is used for acquiring an inside image and an outside image of a rail of the turnout under the condition that the train reaches the turnout position according to the time when the train reaches the turnout position.
Preferably, the switch image acquisition unit includes: the first turnout camera is used for collecting an image of the outer side of a first steel rail of the turnout; the second turnout camera is used for collecting an image of the inner side of the first steel rail of the turnout; the third turnout camera is used for collecting an image of the inner side of the second steel rail of the turnout; and the fourth turnout camera is used for collecting the rail outer side image of the second rail positioned at the turnout.
Preferably, the railway line status inspection system further comprises: and the alarm module is used for alarming when faults exist on the inner side and/or the outer side of the rail of the turnout and alarming when defects exist on the loop line.
Correspondingly, the invention also provides a railway line state inspection method, which comprises the following steps: detecting the speed of a train; acquiring an inside image and an outside image of a track of a railway turnout by adopting a plurality of turnout cameras at the railway turnout according to the speed and prestored kilometer sign information; and judging whether the inside and/or outside of the track of the turnout has faults or not according to the acquired inside and outside images and the pre-stored normal images of the track of the turnout and by adopting a pre-set deep learning target detection model.
Preferably, the railway line status inspection method further comprises: collecting loop line images in real time; and judging whether the loop has defects according to the loop image acquired in real time and the pre-stored loop initial state.
Preferably, the acquiring the track inside image and the track outside image of the railway switch according to the speed and the prestored kilometer post information respectively comprises: judging the position of the train according to the speed and the kilometer post information, thereby determining the time of the train reaching the turnout position; and acquiring the track inner side image and the track outer side image of the turnout by adopting a plurality of turnout cameras under the condition that the train reaches the turnout position according to the time of the train reaching the turnout position.
Preferably, the acquiring the track inside image and the track outside image of the switch by using a plurality of switch cameras includes: acquiring an image of the outer side of a first steel rail of the turnout by adopting a first turnout camera; acquiring an image of the inner side of a first steel rail of the turnout by adopting a second turnout camera; acquiring an image of the inner side of a second steel rail of the turnout by adopting a third turnout camera; and acquiring an image of the outer side of the second steel rail of the turnout by adopting a fourth turnout camera.
Preferably, the railway line status inspection method further comprises: and alarming when faults exist on the inner side and/or the outer side of the rail of the turnout, and alarming when defects exist on the loop line.
The invention collects the track inside image and track outside image of the turnout at the railway turnout by detecting the train speed and prestored kilometer sign information, and judges whether the track inside and/or track outside of the turnout has faults or not by utilizing a deep learning target detection algorithm according to the collected track inside image and track outside image of the turnout and prestored normal image.
Drawings
The accompanying drawings are included to provide a further understanding of embodiments of the invention and are incorporated in and constitute a part of this specification, illustrate embodiments of the invention and together with the description serve to explain, without limitation, the embodiments of the invention. In the drawings:
FIG. 1 is a block diagram of a railroad line status inspection system provided by the present invention;
FIG. 2 is a block diagram of another railroad line status inspection system provided by the present invention; and
fig. 3 is a flowchart of a railway line status inspection method provided by the invention.
Detailed Description
The following describes the detailed implementation of the embodiments of the present invention with reference to the drawings. It should be understood that the detailed description and specific examples, while indicating and illustrating the invention, are not intended to limit the scope of the invention.
Fig. 1 is a block diagram of a railway line status inspection system provided by the present invention, and as shown in fig. 1, the system includes a speed detection module 10, a switch detection module 20, and an image processing module 30.
The speed detection module 10 is arranged on the axle end of a wheel of a train or a motor gearbox and is used for detecting the speed of the train. The speed detection module may utilize a sensor, such as a speed sensor.
The switch detection module 20 comprises a plurality of switch cameras, is arranged at the bottom of a train, and is used for respectively acquiring an inside image and an outside image of a rail of a switch at the railway switch according to the speed of the train and prestored kilometer sign information. The switch detection module 20 firstly calculates the position of the train according to the speed obtained by the speed detection module 10 and the prestored kilometer sign information, namely, judges whether the train is positioned at the switch or when the train is positioned at the switch, and then respectively acquires the track inner side image and the track outer side image of the switch through a plurality of switch cameras under the condition that the train is positioned at the switch. The turnout camera can acquire high-definition images of visual components of the turnout in the running process of the train, and the camera is selected to be suitable for the speed of 120 km/h.
The plurality of switch cameras arranged at the bottom of the train should be arranged at the positions where the inside images and the outside images of the rails of the switch can be shot, and the specific position at the bottom of the train can be set according to the actual situation.
The image processing module 30 is configured to determine whether a fault exists on the inner side and/or the outer side of the switch according to the acquired inner side and outer side images of the switch and the pre-stored normal image and by using a deep learning target detection model. The method comprises the step of comparing and analyzing the acquired track inside image and track outside image of the turnout with the track inside image and track outside image without faults to judge whether the turnout has faults, such as whether the appearance of the turnout structure is abnormal, whether foreign matters exist or not, by adopting a deep learning target detection model.
It should be understood by those skilled in the art that the deep learning target detection model is obtained by training a deep learning algorithm, and the image processing module may train the deep learning target detection model in advance by using training parameters, where the training parameters include an inside-track image and an outside-track image of a switch known to have a fault and a normal image (i.e., an inside-track image and an outside-track image of a switch known to have no fault), and after training the deep learning target detection model by using the training parameters, a deep learning target detection model for determining whether a fault exists inside the track and/or outside the track of the switch is obtained, and the deep learning algorithm, the deep learning target detection model and the training process are all techniques well known in the art and are not described herein.
Fig. 2 is a block diagram of another railway line status inspection system provided by the present invention, and as shown in fig. 2, the system further includes a loop detection module 40.
The loop detection module 40 comprises a loop camera, is arranged at the bottom of the train and is used for acquiring loop images in real time; the image processing module 30 is further configured to determine whether a loop has a defect according to a loop image acquired in real time and a pre-stored loop initial state. The position of the loop camera is any position where the height of the loop can be collected at the bottom of the train.
The loop is a cable which is positioned between two steel rails of the railway line and is in a high-low fluctuation mode, the distance between the loop and the ground is easy to understand, the pre-stored initial state of the loop refers to the loop state when the loop is arranged, namely, the loop is not damaged, and the height of the loop is not changed after the loop is arranged. The detection of whether the loop wire has defects by the loop wire detection module 40 of the present invention includes whether the loop wire is damaged or not, and whether the distance between any position of the loop wire and the ground is changed from the initial state or not, because the loop wire is supported by the support at intervals, the height between the loop wire and the ground is changed in a fluctuation manner as a whole, and the height between the loop wire and the ground of the corresponding part is changed, namely, the height is different from the height in the initial state when the support fails.
In the running process of the train, the loop camera shoots in real time to obtain loop images at any positions, the image processing module 30 compares the loop images obtained by shooting in real time by the loop camera with the initial state of the loop, and the loop is considered to have defects under the following two conditions: the first case, there is a leaky cable case; in the second case, the height of the loop at a certain position is different from the initial state.
As shown in fig. 2, the switch detection module 20 includes a train position determination unit 21 and a switch image acquisition unit 22.
The train position determination unit 21 is used for determining the position of the train according to the speed and the kilometer post information, thereby determining the time when the train reaches the turnout position. It will be appreciated by those skilled in the art that the speed of a train arrives at a particular speed location, and that the speed of a train arrives at the speed of a switch is fixed, since speed of a train is known in advance.
The switch image acquisition unit 22 includes a plurality of switch cameras for acquiring an inside-track image and an outside-track image of a switch in the case where a train arrives at a switch position according to the time when the train arrives at the switch position. The technical scheme provided by the invention is that whether a rail at a turnout position has a fault or not is judged, so that the turnout image acquisition unit 22 acquires an inside image and an outside image of the rail of the turnout according to the time when the train obtained by the train position judgment unit 21 reaches the position where the turnout is located.
More specifically, the switch image acquisition unit 22 includes four switch cameras, which are a first switch camera, a second switch camera, a third switch camera, and a fourth switch camera, respectively.
The first turnout camera is used for collecting an image of the outer side of a first steel rail of the turnout; the second turnout camera is used for collecting an image of the inner side of the first steel rail of the turnout; the third turnout camera is used for collecting an image of the inner side of a second steel rail of the turnout; and the fourth turnout camera is used for collecting the rail outer side image of the second steel rail positioned at the turnout.
Four switch cameras set up in the arbitrary suitable position of train bottom, more specifically, first switch camera sets up the position that can shoot the rail outside image of the first rail of switch in the train bottom, and the second switch camera sets up the position that can shoot the rail inside image of the first rail of switch in the train bottom, and the third switch camera sets up the position that can shoot the rail inside image of the second rail of switch in the train bottom, and the fourth switch camera sets up the position that can shoot the rail outside image of the second rail of switch in the train bottom.
The railway line state inspection system provided by the invention further comprises an alarm module (not shown in the figure), wherein the alarm module is used for alarming when faults exist on the inner side of a rail and/or the outer side of the rail of the turnout, and is used for alarming when defects exist on a loop. Specifically, when there is a problem with information displayed in a certain picture, an alarm is given.
Fig. 3 is a flowchart of a railway line status inspection method provided by the invention, as shown in fig. 3, the method includes:
step S301, detecting the speed of a train;
step S302, respectively acquiring an inside image and an outside image of a track of a railway switch by adopting a plurality of switch cameras at the railway switch according to the speed and prestored kilometer sign information;
step S303, judging whether faults exist on the inner side and/or the outer side of the turnout according to the acquired inner side and outer side images of the turnout and the pre-stored normal images and by adopting a pre-set deep learning target detection model.
The railway line state inspection method provided by the invention further comprises the following steps: collecting loop line images in real time; judging whether the loop has defects according to the loop image acquired in real time and the pre-stored loop initial state.
Wherein, gather the inboard image of rail and the outside image of rail of switch respectively at the railway switch according to speed and the kilometer post information of prestore and include: judging the position of the train according to the speed and kilometer post information, thereby determining the time of the train reaching the turnout position; and acquiring the track inner side image and the track outer side image of the turnout by adopting a plurality of turnout cameras under the condition that the train reaches the turnout position according to the time of the train reaching the turnout position.
Wherein, adopt a plurality of switch cameras to gather the inboard image of rail and the outside image of rail of switch include: acquiring an image of the outer side of a first steel rail of the turnout by adopting a first turnout camera; acquiring an image of the inner side of a first steel rail of the turnout by adopting a second turnout camera; acquiring an image of the inner side of a second steel rail of the turnout by adopting a third turnout camera; and acquiring an image of the outer side of the second steel rail of the turnout by adopting a fourth turnout camera.
The railway line state inspection method provided by the invention further comprises the following steps: the alarm is given in case of a fault on the inside and/or outside of the track of the switch and is used in case of a defect on the loop.
It should be noted that, the specific details and benefits of the method for inspecting the railway line status provided by the present invention are similar to those of the system for inspecting the railway line status provided by the present invention, and are not repeated herein.
The foregoing details of the optional implementation of the embodiment of the present invention have been described in detail with reference to the accompanying drawings, but the embodiment of the present invention is not limited to the specific details of the foregoing implementation, and various simple modifications may be made to the technical solution of the embodiment of the present invention within the scope of the technical concept of the embodiment of the present invention, and these simple modifications all fall within the protection scope of the embodiment of the present invention.
In addition, the specific features described in the above embodiments may be combined in any suitable manner without contradiction. In order to avoid unnecessary repetition, various possible combinations of embodiments of the present invention are not described in detail.
In addition, any combination of various embodiments of the present invention may be performed, so long as the concept of the embodiments of the present invention is not violated, and the disclosure of the embodiments of the present invention should also be considered.
Claims (8)
1. A railroad line status inspection system, the system comprising:
the speed detection module is arranged at the axle end of a wheel of the train or on a motor gear box and is used for detecting the speed of the train;
the turnout detection module comprises a plurality of turnout cameras and is arranged at the bottom of a train and used for respectively acquiring an inside image and an outside image of a railway of the turnout at the railway turnout according to the speed and prestored kilometer sign information; and
the image processing module is used for judging whether the inside and/or the outside of the track of the turnout has faults according to the acquired inside and outside images of the track of the turnout and the pre-stored normal image and by adopting a pre-set deep learning target detection model, wherein the deep learning target detection model is used for judging whether the inside and/or the outside of the track of the turnout has faults or not through comparing and analyzing the acquired inside and outside images of the track of the turnout with the inside and outside images of the track without faults, and the normal image comprises the inside and outside images of the track without faults;
wherein, switch detection module includes:
the train position judging unit is used for judging the position of the train according to the speed and the kilometer post information so as to determine the time of the train reaching the turnout position; and
the turnout image acquisition unit comprises a plurality of turnout cameras and is used for acquiring an inside image and an outside image of a rail of the turnout under the condition that the train reaches the turnout position according to the time when the train reaches the turnout position.
2. The railroad line status inspection system of claim 1, further comprising:
the loop detection module comprises a loop camera, is arranged at the bottom of the train and is used for acquiring loop images in real time;
the image processing module is also used for judging whether the loop has defects according to the loop image acquired in real time and the pre-stored loop initial state.
3. The railroad line status inspection system of claim 1, wherein the switch image acquisition unit comprises:
the first turnout camera is used for collecting an image of the outer side of a first steel rail of the turnout;
the second turnout camera is used for collecting an image of the inner side of the first steel rail of the turnout;
the third turnout camera is used for collecting an image of the inner side of the second steel rail of the turnout; and
and the fourth turnout camera is used for acquiring the rail outer side image of the second rail positioned at the turnout.
4. The railroad line status inspection system of claim 2, further comprising:
and the alarm module is used for alarming when faults exist on the inner side and/or the outer side of the rail of the turnout and alarming when defects exist on the loop line.
5. The railway line state inspection method is characterized by comprising the following steps:
detecting the speed of a train;
acquiring an inside image and an outside image of a track of a railway turnout by adopting a plurality of turnout cameras at the railway turnout according to the speed and prestored kilometer sign information; and
judging whether the inside and/or the outside of the track of the turnout has faults or not according to the acquired inside and outside images and a pre-stored normal image of the turnout and by adopting a pre-set deep learning target detection model, wherein the deep learning target detection model is used for judging whether the inside and/or the outside of the track of the turnout has faults or not by comparing and analyzing the acquired inside and outside images of the turnout with the inside and outside images of the track without faults, and the normal image comprises the inside and outside images of the track without faults;
wherein, according to speed and the kilometer post information of prestore, gather respectively at the railway switch the inboard image of rail of switch and the outside image of rail include:
judging the position of the train according to the speed and the kilometer post information, thereby determining the time of the train reaching the turnout position; and
and acquiring the track inner side image and the track outer side image of the turnout by adopting a plurality of turnout cameras under the condition that the train reaches the turnout position according to the time of the train reaching the turnout position.
6. The railroad line status inspection method of claim 5, further comprising:
collecting loop line images in real time; and
judging whether the loop has defects according to the loop image acquired in real time and the pre-stored loop initial state.
7. The method of claim 5, wherein the acquiring the inside and outside track images of the switch using a plurality of switch cameras comprises:
acquiring an image of the outer side of a first steel rail of the turnout by adopting a first turnout camera;
acquiring an image of the inner side of a first steel rail of the turnout by adopting a second turnout camera;
acquiring an image of the inner side of a second steel rail of the turnout by adopting a third turnout camera; and
and acquiring an image of the outer side of the second steel rail of the turnout by adopting a fourth turnout camera.
8. The railroad line status inspection method of claim 5, further comprising:
and alarming when faults exist on the inner side and/or the outer side of the rail of the turnout, and alarming when defects exist on the loop line.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202211170733.0A CN115610479B (en) | 2022-09-23 | 2022-09-23 | Railway line state inspection system and method |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202211170733.0A CN115610479B (en) | 2022-09-23 | 2022-09-23 | Railway line state inspection system and method |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN115610479A CN115610479A (en) | 2023-01-17 |
| CN115610479B true CN115610479B (en) | 2023-09-15 |
Family
ID=84881095
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202211170733.0A Active CN115610479B (en) | 2022-09-23 | 2022-09-23 | Railway line state inspection system and method |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN115610479B (en) |
Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN202854908U (en) * | 2012-10-12 | 2013-04-03 | 昆明铁路局 | Railway line intelligent inspection system |
| CN105501248A (en) * | 2016-02-16 | 2016-04-20 | 株洲时代电子技术有限公司 | Railway line inspection system |
| CN106794851A (en) * | 2014-10-22 | 2017-05-31 | Hp3真实有限责任公司 | Method for measuring and showing the track geometry shape of track equipment |
| CN110248858A (en) * | 2016-12-07 | 2019-09-17 | 西门子交通有限责任公司 | For in rail traffic the image analysis based on track, in particular for method, equipment and the rail vehicle of the image analysis based on rail in railway traffic, especially rolling stock |
| CN112960014A (en) * | 2021-02-02 | 2021-06-15 | 南京效秀自动化技术有限公司 | Rail transit operation safety online real-time monitoring and early warning management cloud platform based on artificial intelligence |
| CN113104063A (en) * | 2021-06-09 | 2021-07-13 | 成都国铁电气设备有限公司 | Comprehensive detection system and method for network rail tunnel |
Family Cites Families (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US8345948B2 (en) * | 2009-09-11 | 2013-01-01 | Harsco Corporation | Automated turnout inspection |
-
2022
- 2022-09-23 CN CN202211170733.0A patent/CN115610479B/en active Active
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN202854908U (en) * | 2012-10-12 | 2013-04-03 | 昆明铁路局 | Railway line intelligent inspection system |
| CN106794851A (en) * | 2014-10-22 | 2017-05-31 | Hp3真实有限责任公司 | Method for measuring and showing the track geometry shape of track equipment |
| CN105501248A (en) * | 2016-02-16 | 2016-04-20 | 株洲时代电子技术有限公司 | Railway line inspection system |
| CN110248858A (en) * | 2016-12-07 | 2019-09-17 | 西门子交通有限责任公司 | For in rail traffic the image analysis based on track, in particular for method, equipment and the rail vehicle of the image analysis based on rail in railway traffic, especially rolling stock |
| CN112960014A (en) * | 2021-02-02 | 2021-06-15 | 南京效秀自动化技术有限公司 | Rail transit operation safety online real-time monitoring and early warning management cloud platform based on artificial intelligence |
| CN113104063A (en) * | 2021-06-09 | 2021-07-13 | 成都国铁电气设备有限公司 | Comprehensive detection system and method for network rail tunnel |
Also Published As
| Publication number | Publication date |
|---|---|
| CN115610479A (en) | 2023-01-17 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN106061822B (en) | Vehicle imaging systems and method | |
| CN107433962B (en) | Method and system for track traffic fault monitoring and intelligent early warning | |
| KR101672472B1 (en) | Comprehensive diagnosing and managementing system of a railcar | |
| KR101111569B1 (en) | Monitering System of Railroad Facilities using Railway Vehicle | |
| US8942426B2 (en) | On-train rail track monitoring system | |
| CN108491758B (en) | Track detection method and robot | |
| CN102941864B (en) | Train loading state high-definition monitoring and overloading detection method | |
| KR101701160B1 (en) | Cantilever defect inspection system | |
| CN105115605A (en) | Track train infrared detection system and detection method | |
| KR20140031541A (en) | Defect inspection system of overhead contact line | |
| CN105608822A (en) | Railway perimeter intrusion vibration fiber alarm method and device | |
| CN105905133A (en) | Automatic monitoring alarm method and system for railway line obstacle | |
| CN115610479B (en) | Railway line state inspection system and method | |
| Berry et al. | High speed video inspection of joint bars using advanced image collection and processing techniques | |
| KR20090091837A (en) | System and method to monitor a wheel of train | |
| KR20090085214A (en) | System and method to monitor a rail | |
| KR20090085221A (en) | System and method to monitor a rail | |
| CN110626380B (en) | Motor train unit positive line detection method | |
| KR101463797B1 (en) | Method and apparatus for diagnosing railway by using driving noise of railway vehicle | |
| JPH1016777A (en) | Heating part detector of track equipment | |
| Gibert-Serra et al. | A machine vision system for automated joint bar inspection from a moving rail vehicle | |
| CN114348054A (en) | Railway turnout disease monitoring method, device and system | |
| CN116124771A (en) | Method for identifying loosening faults of central anchoring rope of contact net | |
| CN111076750B (en) | Device and method for detecting looseness of catenary dropper wire clamp | |
| KR20110082401A (en) | Automatic and diagnosing apparatus of a railcar |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| TA01 | Transfer of patent application right | ||
| TA01 | Transfer of patent application right |
Effective date of registration: 20230809 Address after: 100000 floor 11, block B, No. 22, Shangdi Information Road, Haidian District, Beijing Applicant after: BEIJING GTV TECHNOLOGY DEVELOPMENT Co.,Ltd. Applicant after: GUANGZHOU METRO GROUP Co.,Ltd. Address before: 100000 floor 11, block B, No. 22, Shangdi Information Road, Haidian District, Beijing Applicant before: BEIJING GTV TECHNOLOGY DEVELOPMENT Co.,Ltd. |
|
| GR01 | Patent grant | ||
| GR01 | Patent grant |