A vehicle body positioning method and positioning device used in a tunnel

Abstract

The present invention relates to the field of tunnel positioning, and aims to provide a defect positioning device for use in a tunnel. The present invention comprises a vehicle body, a GPS module, a signal processing board and an industrial computer. A roof 3D camera is arranged on the top of the vehicle body, and the roof 3D camera is used to collect device images on a contact network in the tunnel. A bottom 3D camera is arranged on the bottom of the vehicle body, and the bottom 3D camera is used to collect device images on a track in the tunnel. The GPS module is used to obtain longitude and latitude data of the vehicle body in the tunnel. The GPS module is connected to the signal processing board, and the industrial computer is respectively connected to the roof 3D camera, the bottom 3D camera and the signal processing board.

Description

Technical Field

[0001] The invention relates to the field of railway maintenance, and in particular to a vehicle body positioning method and a positioning device used in a tunnel. Background Art

[0002] At present, the positioning schemes adopted by the overhead contact network and track automatic monitoring system installed on subway vehicles mainly include: GPS / Beidou module, speed encoder, Doppler radar, electronic tag, etc. Among them, the GPS / Beidou module works better outside the tunnel. The signal is strong only near the subway station in the tunnel. There is no GPS / Beidou signal in the area between two stations. The speed encoder is usually installed on the vehicle axle. The speed encoder will output several pulse signals for each rotation of the wheel. However, due to the serpentine motion of the wheel during driving (as shown in Figure (1)), the vehicle mileage calculated by this scheme has a large deviation. The positioning scheme of the electronic tag requires laying several tags along the railway line, which requires a large amount of construction and is inconvenient for maintenance. The serpentine motion of the wheel will not cause positioning errors to the Doppler radar positioning scheme, and there is no need for engineering construction along the railway line. However, this scheme only calculates the mileage information of the vehicle, and cannot confirm the initial position of the wheel or convert the mileage data into kilometer mark, pole number and other positioning information commonly used by railway maintenance personnel. In addition, the cost of this positioning scheme is relatively high.

[0003] Therefore, a method is needed to locate the vehicle body in the tunnel, which can effectively solve the problems of no GPS signal between the two platforms in the tunnel and the cumulative error caused by the serpentine motion of the wheels, and does not require engineering construction along the railway. It can provide higher positioning accuracy while maintaining a low cost. Summary of the invention

[0004] The purpose of the present invention is to provide a vehicle body positioning device and method for use in a tunnel, which realizes detection and positioning of key components by collecting cross-sectional (section) data of key components of the contact network and key components of the track in the subway tunnel, and realizes accurate positioning of the subway vehicle by combining line basic data mapping. The present invention has a reasonable structure, ingenious design, and is suitable for promotion;

[0005] To achieve the above-mentioned purpose, the technical solution adopted by the present invention is: a vehicle body positioning device for use in a tunnel, characterized in that the vehicle body positioning device for use in a tunnel includes a vehicle body, a GPS module, a signal processing board and an industrial computer. A roof 3D camera is arranged on the top of the vehicle body, and the roof 3D camera is used to collect images of a contact network device in the tunnel. A bottom 3D camera is arranged on the bottom of the vehicle body, and the bottom 3D camera is used to collect images of a track device in the tunnel. The GPS module is used to obtain the longitude and latitude data of the vehicle body in the tunnel. The GPS module is connected to the signal processing board, and the industrial computer is respectively connected to the roof 3D camera, the bottom 3D camera and the signal processing board.

[0006] Preferably, at least one roof 3D camera is arranged on the roof of the vehicle body.

[0007] Preferably, at least one underbody 3D camera is arranged on the underbody of the vehicle.

[0008] On the other hand, a defect location method for a tunnel includes the above-mentioned defect location device for a tunnel, and comprises the following steps:

[0009] Step 1: The tunnel contains several fixed stations. When the vehicle passes through the station, the GPS module on the vehicle will obtain the latitude and longitude data P0 of the vehicle;

[0010] Step 2: When the vehicle body is traveling on the track in the tunnel, the 3D camera on the roof acquires the image of the device on the contact network in the tunnel and sends it to the industrial computer, and the 3D camera under the vehicle acquires the image of the device on the track in the tunnel and sends it to the industrial computer;

[0011] Step 3: The industrial computer pre-stores the original device image data on the contact network and the original device image data on the track in the tunnel. When the acquired device image data is greater than the threshold value of the original device image data, the position of the vehicle body at this time is determined by superimposing the longitude and latitude data P0 of the vehicle body;

[0012] In step 2, the device on the contact network in the tunnel includes a busbar, a contact wire, a support device and an anchor section joint, and the busbar contact wire, the support devices and the anchor section joints are all spaced at a fixed distance. The device on the track in the tunnel includes a ballast, a transponder and an approach plate.

[0013] In step 1, the industrial computer also stores a latitude and longitude basic data mapping table T, which contains the latitude and longitude values ​​of several stations. The calculation formula for obtaining the station closest to the vehicle body is:

[0014]

[0015] The starting station of the vehicle is calculated using the Euclidean distance, and the calculation formula is:

[0016]

[0017] In the above formula, N0 represents latitude information, E0 represents longitude information, that is, P0=(N0, E0), P0 obtained by the GPS module is compared with the longitude and latitude basic data mapping table T, T={(N1, E1), (N2, E2), …, (N n ,E n )}, Dist gets the starting station of the vehicle by calculating P0 and T1;

[0018] In step 3, a similarity judgment model is pre-stored in the industrial computer, and the device image acquired by the 3D camera is used as input, and the location data of the vehicle body is output;

[0019] The method of the similarity judgment model is that the shape outline of the device image acquired by the 3D camera is S, the original device image threshold pre-stored in the industrial computer includes the shape outline of the original device as S0 and the threshold Thr, and the cosine similarity is calculated, and the calculation formula is:

[0020]

[0021] In the formula, for The similarity between S0 and is the shape outline of the device image acquired by the 3D camera most recently. When the value of is greater than the threshold Thr, it is concluded that the vehicle body has passed the i-th device; the industrial computer stores basic data mapping tables of several device types.

[0022] Compared with the prior art, the present invention has the following beneficial effects:

[0023] 1. Automatically collect data and accurately locate the position of the vehicle in the tunnel;

[0024] 2. Simple maintenance, the collection frequency can be adjusted according to the corresponding tunnel. BRIEF DESCRIPTION OF THE DRAWINGS

[0025] FIG1 is a schematic diagram of a vehicle positioning method for use in a tunnel;

[0026] FIG2 is a schematic diagram of a vehicle positioning device used in a tunnel according to an embodiment of the present invention;

[0027] FIG3 is a schematic diagram showing a mapping of the basic data of longitude and latitude of stations along the line in an embodiment of the present invention;

[0028] FIG4 is a physical diagram of the busbar contact line in an embodiment of the present invention;

[0029] FIG5 is a cross-sectional view of a busbar contact line captured by a 3D camera in an embodiment of the present invention;

[0030] FIG6 is a physical diagram of a contact network support device in an embodiment of the present invention;

[0031] FIG7 is a cross-sectional view of a support device for 3D camera acquisition in an embodiment of the present invention;

[0032] FIG8 is a schematic diagram of a basic data mapping diagram of a support device in an embodiment of the present invention;

[0033] FIG9 is a physical diagram of the contact network anchor section joint in an embodiment of the present invention;

[0034] FIG10 is a diagram showing cross-sectional data of the anchor segment joint region collected by a 3D camera in an embodiment of the present invention;

[0035] FIG11 is a schematic diagram showing a mapping of anchor segment joint basic data in an embodiment of the present invention;

[0036] FIG12 is a schematic diagram of a 3D camera scanning a track bed section in an embodiment of the present invention;

[0037] FIG13 is a physical picture of a subway track bed in an embodiment of the present invention;

[0038] FIG14 is a diagram of the cross-section data of the track bed collected by a 3D camera in an embodiment of the present invention;

[0039] FIG15 is a physical picture of a transponder in a subway tunnel according to an embodiment of the present invention;

[0040] FIG16 is a diagram of transponder cross-sectional data collected by a 3D camera in an embodiment of the present invention;

[0041] FIG. 17 is a schematic diagram of a mapping representation of basic transponder data in an embodiment of the present invention;

[0042] FIG18 is a physical diagram of a subway platform approach plate in an embodiment of the present invention;

[0043] FIG19 is a diagram of the cross-sectional data of the approach disk collected by a 3D camera in an embodiment of the present invention;

[0044] FIG. 20 is a schematic diagram of a basic data mapping diagram close to the disk in an embodiment of the present invention. DETAILED DESCRIPTION

[0045] Below in conjunction with the appended Figures 1 to 20, clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of them. Based on the embodiments of the present invention, all other implementations obtained by ordinary technicians in this field without creative work.

[0046] In the description of the present invention, it should be understood that the terms "counterclockwise", "clockwise", "longitudinal", "lateral", "up", "down", "front", "back", "left", "right", "vertical", "horizontal", "top", "bottom", "inside", "outside", etc., indicating directions or positional relationships, are based on the directions or positional relationships shown in the accompanying drawings, and are only for the convenience of describing the present invention, and do not indicate or imply that the device or element referred to must have a specific direction, be constructed and operated in a specific direction, and therefore should not be understood as a limitation on the present invention.

[0047] Figure 1 A structural diagram of a defect location method for a tunnel according to the present invention;

[0048] Embodiment 1:

[0049] A vehicle positioning device for use in a tunnel comprises a vehicle body, a GPS module, a signal processing board and an industrial computer. A roof 3D camera is arranged on the top of the vehicle body, and the roof 3D camera is used to collect images of devices on a contact network in the tunnel. A bottom 3D camera is arranged on the bottom of the vehicle body, and the bottom 3D camera is used to collect images of devices on a track in the tunnel. The GPS module is used to obtain longitude and latitude data of the vehicle body in the tunnel. The GPS module is connected to the signal processing board, and the industrial computer is respectively connected to the roof 3D camera, the bottom 3D camera and the signal processing board.

[0050] It is worth noting that at least one roof 3D camera is arranged on the roof of the vehicle body, and at least one bottom 3D camera is arranged on the bottom of the vehicle body.

[0051] It is worth mentioning that please refer to Figure 2 One or more 3D cameras can be installed only on the roof, one or more 3D cameras can be installed only on the bottom of the vehicle, or one or more 3D cameras can be installed on both the roof and the bottom of the vehicle to detect and identify key components on the contact network and track, thereby realizing the positioning of subway vehicles. It can be used on subway operating vehicles, as well as subway inspection vehicles and subway engineering vehicles.

[0052] Embodiment 2:

[0053] A method for positioning a vehicle body in a tunnel, based on Embodiment 1, comprises the following steps:

[0054] Step 1: There are several fixed stations in the tunnel. When the vehicle passes through a station, the GPS module on the vehicle will obtain the latitude and longitude data P0 of the station closest to the vehicle;

[0055] Step 2: When the vehicle body is traveling on the track in the tunnel, the roof 3D camera obtains the device image on the contact network in the tunnel and sends it to the industrial computer, and the body 3D camera obtains the device image on the track in the tunnel and sends it to the industrial computer;

[0056] Step 3: The industrial computer has pre-stored therein the original device image threshold on the contact network and the original device image threshold on the track in the tunnel. When the acquired device image data is greater than the original device image threshold, the position of the vehicle body at this time is determined by superimposing the latitude and longitude data P0 of the station.

[0057] It is worth noting that in step 2, the device on the contact network in the tunnel includes a bus contact line, a supporting device and an anchor section joint, and there is a fixed distance between the bus contact lines, the supporting devices and the anchor section joints. The device on the track in the tunnel includes a ballast, a transponder and an approach plate.

[0058] It is worth noting that in step 1, the industrial computer also stores a latitude and longitude basic data mapping table T, which contains the latitude and longitude values ​​of several stations. The calculation formula for obtaining the station closest to the vehicle body is:

[0059]

[0060] The starting station of the vehicle is calculated using the Euclidean distance, and the calculation formula is:

[0061]

[0062] In the above formula, N0 represents latitude information, E0 represents longitude information, that is, P0=(N0, E0), P0 obtained by the GPS module is compared with the longitude and latitude basic data mapping table T, T={(N1, E1), (N2, E2), …, (N n ,E n )}, Dist gets the starting station of the vehicle by calculating P0 and T1.

[0063] It is worth noting that in step 3, a similarity judgment model is pre-stored in the industrial computer, and the device image acquired by the 3D camera is used as input, and the location data of the vehicle body is output.

[0064] It is worth noting that the method of the similarity judgment model is that the shape outline of the device image acquired by the 3D camera is S, the original device image threshold pre-stored in the industrial computer includes the shape outline of the original device as S0 and the threshold Thr, and the cosine similarity is calculated, and the calculation formula is:

[0065]

[0066] In the formula, for The similarity between S0 and is the shape outline of the device image acquired by the 3D camera most recently. When the value of is greater than the threshold Thr, it is concluded that the vehicle body has passed the i-th device.

[0067] It is worth noting that the industrial computer stores several basic data mapping tables of device types, and the differences between several threshold values ​​Thr contained in each basic data mapping table are in increasing relationship.

[0068] It is worth mentioning that the roof-mounted 3D camera is used to obtain three-dimensional information of contact network components such as contact wires, buses, and supporting devices on the roof of electric locomotives; the GPS module is used to obtain GPS longitude and latitude information near the platform in the tunnel, so as to determine the initial starting position of the electric locomotive and whether it has arrived at a certain station; the signal processing board is connected to the GPS module for signal acquisition and processing; the bottom 3D camera is used to obtain three-dimensional information of track components such as sleepers, transponders, and approach plates; the industrial computer in the car is used for three-dimensional data analysis, comparison, GPS longitude and latitude mapping, etc.

[0069] It is worth noting that the latitude and longitude information P0 of the station where the vehicle is currently located is obtained using the rooftop GPS module. N0 represents the latitude information and E0 represents the longitude information, then P0=(N0,E0). P0 is compared with the latitude and longitude basic data mapping table T={(N1,E1), (N2,E2), …, (Nn,En)} previously entered into the industrial computer. The station P that is closest to the mapping table T is the station where the vehicle is currently located, that is:

[0070]

[0071] Here, Min means taking the minimum, and Dist|| indicates the distance calculation formula, which can be Euclidean distance, Chebyshev distance, Manhattan distance, Mahalanobis distance, etc. Here, taking Euclidean distance as an example, the distance calculation formula between P0 and T1 is: Euclidean distance calculation vehicle starting station:

[0072]

[0073] Please refer to Figure 3, Figure 3 It shows the schematic diagram of the basic data mapping of longitude and latitude of stations along the line.

[0074] It is worth noting that the cross-sectional data of the overhead contact network directly above the vehicle is continuously collected using the roof 3D camera (the sampling frequency of the 3D camera can be set to a fixed value such as 100Hz, 1000Hz based on experience, or can be adjusted adaptively according to the vehicle speed to ensure that 3D data is collected at least once every 1mm or 10mm). Under normal circumstances, the main equipment of the overhead contact network in the tunnel is the busbar and the contact wire. Please refer to Figure 4 Therefore, the cross-sectional shape of the contact network obtained by the 3D camera is as follows Figure 5 shown.

[0075] It is worth mentioning that a supporting device appears every 8 meters or so on the rigid contact network in the subway tunnel. Figure 6 Obviously, the cross-sectional shape of the support device captured by the 3D camera is completely different from the cross-sectional shape of the busbar and contact wire, as shown in Figure 2. Figure 7 As shown in the figure, assume that the current cross-section shape profile of the contact network collected by the roof 3D camera is S, and the cross-section model shape profile of the support device stored in the industrial computer is S0. If the similarity between the two If it is greater than a certain threshold Thr, it is considered that the subway vehicle has currently passed through 1 support device. The similarity calculation here can use cosine similarity, Jacobi similarity, Pearson correlation coefficient, etc. Here, taking cosine similarity as an example, the similarity calculation formula between S and S0 is:

[0076]

[0077] According to the basic data mapping table of the supporting device stored in the industrial computer in advance, the 100-meter positioning information of the current subway vehicle location can be mapped. Please refer to Figure 8 , Figure 8 Provides a schematic diagram of the basic data mapping for the supporting device.

[0078] It is worth noting that in the subway tunnel, there is an anchor joint every 200 meters or so in the rigid contact network. Fig. 9 Obviously, the cross-sectional shape of the anchor joint captured by the 3D camera is completely different from the cross-sectional shape of the busbar, contact line, and support suspension, as shown in Figure 2. Fig.10As shown in the figure, the cross-sectional data of the current anchor segment joint area collected by the 3D camera is calculated with the cross-sectional model data of the anchor segment joint stored in advance in the industrial computer. If it exceeds a certain threshold, it is considered that the subway vehicle has currently passed through an anchor segment joint area. The similarity calculation here can be performed using cosine similarity, Jacobi similarity, Pearson correlation coefficient, etc. According to the anchor segment joint basic data mapping table stored in advance in the industrial computer, the 100-meter mark positioning information of the current subway vehicle location can be mapped, such as Fig.11 As shown, Fig.11 Schematic diagram of anchor segment joint base data mapping.

[0079] It is worth noting that the cross-sectional data of the roadbed under the vehicle is obtained by using the 3D camera under the vehicle. The schematic diagram of the cross-sectional data of the roadbed scanned by the 3D camera is as follows: Fig.12 As shown in Figure 1. Under normal circumstances, domestic subway tunnels have ballast-free tracks, without sleepers, ballast, etc. Fig.13 As shown in Figure 2. Obviously, the cross-sectional shape of the track bed obtained by the 3D machine is as follows: Fig.14 shown.

[0080] It is worth noting that there is a transponder every 1 km on the subway line. Fig.15 Obviously, the cross-sectional shape of the transponder captured by the 3D camera is completely different from the cross-sectional shape of the roadbed, as shown in Fig.16 As shown,

[0081] The current transponder cross-section data collected by the 3D camera is calculated similarly to the transponder cross-section model data stored in the industrial computer in advance. If it exceeds a certain threshold, it is considered that the subway vehicle has passed through a transponder. The similarity calculation here can use cosine similarity, Jacobi similarity, Pearson correlation coefficient, etc. According to the transponder basic data mapping table stored in the industrial computer in advance, the 100-meter mark positioning information of the current subway vehicle location can be mapped. Please refer to Fig.17 , Fig.17 Maps representations for transponder base data.

[0082] It is worth noting that there are two approach plates at fixed positions on each platform of the subway line. Fig.18 Obviously, the cross-sectional shape of the transponder captured by the 3D camera is different from the cross-sectional shape of the ballast and the transponder, as shown in Figure 2. Fig.19 As shown in the figure, the current approach disk section data collected by the 3D camera is similar to the approach disk section model data stored in the industrial computer. If it exceeds a certain threshold, it is considered that the subway vehicle has passed a transponder. The similarity calculation here can use cosine similarity, Jacobi similarity, Pearson correlation coefficient, etc. According to the approach disk basic data mapping table stored in the industrial computer in advance, the 100-meter mark positioning information of the current subway vehicle location can be mapped, such as Fig. 20 As shown, Fig. 20 A schematic diagram of the underlying data map for close proximity.

[0083] To sum up, the implementation principle of the present invention is: the signal in the tunnel is strong only near the subway station, and there is no GPS / Beidou signal at all in the area between the two stations. By obtaining the GPS location information of the station closest to the vehicle body and superimposing the distance of the position of the device at a specific position in the tunnel, the determined position of the vehicle body in the tunnel at this time is obtained.

Claims

1. A method for positioning a vehicle in a tunnel, the method being adopted in a vehicle positioning device in a tunnel, characterized in that: The vehicle positioning device for use in a tunnel comprises a vehicle body, a GPS module, a signal processing board and an industrial computer. A roof 3D camera is arranged on the top of the vehicle body, and the roof 3D camera is used to collect images of a contact network device in the tunnel. A bottom 3D camera is arranged on the bottom of the vehicle body, and the bottom 3D camera is used to collect images of a track device in the tunnel. The GPS module is used to obtain the longitude and latitude data of the vehicle body in the tunnel. The GPS module is connected to the signal processing board, and the industrial computer is respectively connected to the roof 3D camera, the bottom 3D camera and the signal processing board; at least one roof 3D camera is arranged on the roof of the vehicle body; at least one bottom 3D camera is arranged on the bottom of the vehicle body; The method comprises the steps of: Step 1: The tunnel contains several fixed stations. When the vehicle passes through the station, the GPS module on the vehicle will obtain the latitude and longitude data P0 of the vehicle; Step 2: When the vehicle body is traveling on the track in the tunnel, the 3D camera on the roof acquires the image of the device on the contact network in the tunnel and sends it to the industrial computer, and the 3D camera under the vehicle acquires the image of the device on the track in the tunnel and sends it to the industrial computer; Step 3: The industrial computer pre-stores the original device image data on the contact network and the original device image data on the track in the tunnel. When the acquired device image data is greater than the threshold value of the original device image data, the position of the vehicle body at this time is determined by superimposing the longitude and latitude data P0 of the vehicle body; In step 2, the devices on the contact network in the tunnel include a busbar, a contact wire, a support device and an anchor section joint, and the busbars, the contact wires, the support devices and the anchor section joints are all spaced at a fixed distance, and the devices on the track in the tunnel include a ballast, a transponder and an approach plate; In step 1, the industrial computer also stores a latitude and longitude basic data mapping table T, which contains the latitude and longitude values ​​of several stations. The calculation formula for obtaining the station closest to the vehicle body is: The starting station of the vehicle is calculated using the Euclidean distance, and the calculation formula is: In the above formula, N0 represents latitude information, E0 represents longitude information, that is, P0=(N0, E0), P0 obtained by the GPS module is compared with the longitude and latitude basic data mapping table T, T={(N1, E1), (N2, E2), …, (N n ,E n )}, Dist gets the starting station of the vehicle by calculating P0 and T1; In step 3, a similarity judgment model is pre-stored in the industrial computer, and the device image acquired by the 3D camera is used as input, and the location data of the vehicle body is output; The method of the similarity judgment model is that the shape outline of the device image acquired by the 3D camera is S, the original device image threshold pre-stored in the industrial computer includes the shape outline of the original device as S0 and the threshold Thr, and the cosine similarity is calculated, and the calculation formula is: In the formula, for The similarity between S0 and is the shape outline of the device image most recently acquired by the 3D camera. When the value of is greater than the threshold Thr, it is concluded that the vehicle body has passed the i-th device; the industrial computer stores a basic data mapping table of several device types; The device image includes an image of the bus, an image of the contact line, an image of the support device, an image of the anchor section joint, an image of the roadbed, an image of the transponder, and an image of the approach plate. The device image captured by the 3D camera is similar to the device model data pre-stored in the industrial computer. If it exceeds a set threshold, it is considered that the subway vehicle has currently passed through one device. The similarity calculation here adopts cosine similarity. According to the device basic data mapping table pre-stored in the industrial computer, the 100-meter mark positioning information of the current subway vehicle location is mapped.

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