CN115071785A - Online updating method for urban rail transit signals - Google Patents
Online updating method for urban rail transit signals Download PDFInfo
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- CN115071785A CN115071785A CN202210752996.6A CN202210752996A CN115071785A CN 115071785 A CN115071785 A CN 115071785A CN 202210752996 A CN202210752996 A CN 202210752996A CN 115071785 A CN115071785 A CN 115071785A
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- 238000000034 method Methods 0.000 title claims abstract description 24
- 230000006698 induction Effects 0.000 claims abstract description 73
- 238000003062 neural network model Methods 0.000 claims abstract description 25
- 238000012549 training Methods 0.000 claims description 10
- 238000012937 correction Methods 0.000 description 8
- 238000010586 diagram Methods 0.000 description 6
- 238000004364 calculation method Methods 0.000 description 3
- 238000013528 artificial neural network Methods 0.000 description 2
- 230000008859 change Effects 0.000 description 2
- 230000000694 effects Effects 0.000 description 2
- 238000006467 substitution reaction Methods 0.000 description 2
- 238000005299 abrasion Methods 0.000 description 1
- 238000009825 accumulation Methods 0.000 description 1
- 230000005540 biological transmission Effects 0.000 description 1
- 238000010276 construction Methods 0.000 description 1
- 238000005259 measurement Methods 0.000 description 1
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B61—RAILWAYS
- B61L—GUIDING RAILWAY TRAFFIC; ENSURING THE SAFETY OF RAILWAY TRAFFIC
- B61L25/00—Recording or indicating positions or identities of vehicles or trains or setting of track apparatus
- B61L25/02—Indicating or recording positions or identities of vehicles or trains
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B61—RAILWAYS
- B61L—GUIDING RAILWAY TRAFFIC; ENSURING THE SAFETY OF RAILWAY TRAFFIC
- B61L27/00—Central railway traffic control systems; Trackside control; Communication systems specially adapted therefor
- B61L27/40—Handling position reports or trackside vehicle data
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B61—RAILWAYS
- B61L—GUIDING RAILWAY TRAFFIC; ENSURING THE SAFETY OF RAILWAY TRAFFIC
- B61L27/00—Central railway traffic control systems; Trackside control; Communication systems specially adapted therefor
- B61L27/50—Trackside diagnosis or maintenance, e.g. software upgrades
- B61L27/53—Trackside diagnosis or maintenance, e.g. software upgrades for trackside elements or systems, e.g. trackside supervision of trackside control system conditions
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Abstract
The invention discloses an online updating method of urban rail transit signals, which is suitable for scenes that new and old positioning equipment coexist when existing line signals are disassembled, and comprises the following steps: obtaining the position of the train based on the crossed induction loop and obtaining the position of the train based on the transponder; recording the real position of each crossed induction loop crossing point through a vehicle-mounted ATP (automatic train protection) and obtaining the non-real position of the train based on vehicle-mounted speed measuring equipment and a transponder; calculating the positioning error of the transponder when passing through each intersection of the cross induction loop lines according to the real position and the non-real position; maintaining the normal operation of the train by adopting the position obtained by the responder; inputting the running data of the train into a neural network model to obtain a positioning error; and compensating the position of the train obtained by the transponder by adopting the positioning error. The invention utilizes the old positioning equipment to improve the positioning precision of the new positioning equipment.
Description
Technical Field
The invention relates to the technical field of electric digital processing, in particular to an online updating method for urban rail transit signals.
Background
The disassembly of the subway line is basically to disassemble partial lines of the existing line, and to classify the new line or another existing line to form two completely independent lines. And the existing lines of the subway are all important main lines for urban planning, and have the function of no substitution in urban rail transit.
Because when dismantling the transformation construction to existing line, the circumstances that new and old signal equipment coexisted can appear, only can utilize old equipment to guarantee the normal operation of train daytime, debugs new equipment evening. After debugging is successful and normal operation is carried out for a certain time and is stable, the old equipment is dismantled, and the new equipment is directly used for operation.
In the signal equipment of track traffic, train positioning equipment plays crucial effect, and current solution of disassembling only keeps a positioning device, adopts the positioning strategy that this positioning device provided promptly, but single positioning strategy has its own inherent error and limitation for positioning accuracy can not further promote.
Disclosure of Invention
The invention provides an online updating method of urban rail transit signals, which is used for improving the positioning accuracy of new positioning equipment by using old positioning equipment in a scene that the new positioning equipment and the old positioning equipment coexist when existing line signals are disassembled.
The invention provides an online updating method of urban rail transit signals, which is suitable for scenes that new positioning equipment and old positioning equipment coexist when existing line signals are disassembled, wherein the old positioning equipment is a cross induction loop, and the new positioning equipment is a transponder;
the method comprises the following steps:
obtaining the position of the train based on the crossed induction loop, obtaining the position of the train based on the transponder, and maintaining the normal operation of the train only by adopting the position obtained by the crossed induction loop;
recording the real position of each crossed induction loop crossing point through the vehicle-mounted ATP, and obtaining the non-real position of the train based on the vehicle-mounted speed measuring equipment and the transponder by the vehicle-mounted ATP; the cross point of the cross induction loop is different from the setting position of the transponder; calculating the positioning error of the vehicle-mounted ATP based on the vehicle-mounted speed measuring equipment and the transponder when each cross induction loop intersection passes through according to the real position and the non-real position;
training a neural network model by taking the positioning error passing through each cross induction loop intersection as a label and the running data of the train as an input data sample;
after the crossed induction loop is removed, maintaining the normal running of the train by adopting the position obtained by the transponder; inputting the running data of the train to the neural network model to obtain an output positioning error;
and compensating the position of the train obtained by the responder by adopting the output positioning error to obtain an updated positioning signal.
The method is suitable for a scene that new and old positioning equipment coexist during existing line signal disassembly, the old positioning equipment is a cross induction loop, the new positioning equipment is a transponder, the position of the train is obtained based on the cross induction loop, the position of the train is obtained based on the transponder, and the train is positioned only by adopting the cross induction loop during the train operation period, so that the normal operation of the train is ensured. Recording the real position of each crossed induction loop crossing point and the non-real position of the train obtained on the basis of the vehicle-mounted speed measuring equipment and the transponder; when the vehicle-mounted speed measuring equipment passes through the cross induction loop intersection, the real position can be obtained, but the vehicle-mounted speed measuring equipment does not pass through the transponder at the moment, and the non-real position (accumulated error from the real position) obtained by combining the position of the previous transponder with the vehicle-mounted speed measuring equipment and the line database is still obtained.
And calculating the positioning error of the vehicle-mounted ATP based on the vehicle-mounted speed measuring equipment and the transponder when the vehicle-mounted ATP passes through each cross point of the cross induction loop according to the real position and the non-real position. Training a neural network model by taking a positioning error passing through each cross induction loop intersection as a label and taking the running data of the train as an input data sample; the neural network model represents the logic of the positioning error and operational data of the transponder as it passes through each intersection of the cross sense loops.
After the crossed induction loop is removed, positioning the train by adopting a transponder train during the running period; according to the positioning logic of the transponders, a real position can be obtained when the train passes through each transponder, but then a non-real position can be obtained by combining the vehicle-mounted speed measuring equipment and a line database, so that the running data of the train is input into the neural network model to obtain an output positioning error; the position of the train obtained by the responder is compensated by the outputted positioning error, so that the train can be compensated for once based on the cross induction loop before passing through the next responder, and when the train passes through the next responder, the train is compensated based on the real position of the next responder, so that the positioning precision can be integrally improved in the scene of positioning by the responder.
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In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, and it is obvious that the drawings in the following description are some embodiments of the present invention, and other drawings can be obtained by those skilled in the art without creative efforts.
FIG. 1 is a schematic diagram of positioning and calibration using a transponder according to an embodiment of the present invention;
fig. 2 is a flowchart of an online updating method for urban rail transit signals according to an embodiment of the present invention;
FIG. 3 is a schematic diagram of a transponder incorporating a cross-sense loop according to an embodiment of the present invention;
fig. 4 is a schematic diagram of positioning using a transponder according to an embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the technical solutions of the present invention will be clearly and completely described below. It is to be understood that the described embodiments are merely exemplary of the invention, and not restrictive of the full scope of the invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
In the description of the present invention, it should be noted that the terms "center", "upper", "lower", "left", "right", "vertical", "horizontal", "inner", "outer", etc., indicate orientations or positional relationships based on the orientations or positional relationships shown in the drawings, and are only for convenience of description and simplicity of description, but do not indicate or imply that the device or element being referred to must have a particular orientation, be constructed and operated in a particular orientation, and thus, should not be construed as limiting the present invention. Furthermore, the terms "first," "second," and "third" are used for descriptive purposes only and are not to be construed as indicating or implying relative importance.
In the description of the present invention, it should also be noted that, unless otherwise explicitly stated or limited, the terms "mounted," "connected," and "connected" are to be construed broadly, e.g., as being fixed or detachable or integrally connected; can be mechanically or electrically connected; they may be connected directly or indirectly through intervening media, or they may be interconnected between two elements. The specific meanings of the above terms in the present invention can be understood in specific cases to those skilled in the art.
For the purpose of illustrating the method provided by the present invention, prior art positioning strategies for cross-induction loops and transponders will be described with priority.
1) Positioning strategy of cross induction loop wire: crossing induction loops are laid between the rails along the track, crossing points (namely absolute position reference points) are arranged on the loops at intervals, when a train passes through the crossing points, ground equipment transmits phase change information of the crossing points of the induction loops, and vehicle-mounted equipment combines the positions of the crossing points and a line database to obtain the real position of the train on a line.
2) Positioning strategy of the transponder: the transponders are arranged on the track edge line at certain intervals and are used as absolute position reference points, and the data information on the transponders can be read when the train passes through each transponder, so that the real position is obtained, and the point-type positioning of the train is realized.
The transponder and the cross induction loop have the common feature that between two transponders or two cross induction loops, because there is no real position, the estimated and unreal position can be obtained only by combining the vehicle-mounted speed measuring equipment and the line database on the basis of the intersection point of the last transponder or cross induction loop. And when the next transponder or the cross point of the cross induction loop is passed, the correction is carried out. Taking a transponder as an example, fig. 1 shows a schematic diagram of positioning and correction using a transponder. The distance between adjacent transponders is referred to as the link distance. Because the measurement error of the speed measuring equipment, the wheel diameter parameter error and the calculation error caused by wheel idling and skidding exist objectively and are difficult to eliminate, the error-free train speed measuring and distance measuring method comprehensively forms the error-free train speed measuring and distance measuring method, wherein the distance measuring error can be accumulated along with the train chain distance, and a positive error line and a negative error line are presented. It can be seen that currently only error correction is possible while passing by the transponder, requiring more, denser transponders to be installed to reduce the error accumulation, which undoubtedly increases the cost.
The embodiment of the invention provides an online updating method of urban rail transit signals, which is suitable for a scene that new and old positioning equipment coexist when existing line signals are disassembled, wherein the old positioning equipment is a cross induction loop, and the new positioning equipment is a transponder. When the existing line is disassembled, the old positioning equipment (namely, the cross induction loop line) needs to be updated to the new positioning equipment (namely, the transponder). The transponder is first deployed and during normal daytime train operation, the train location is still performed using the cross induction loop. After the newly laid transponder is debugged, the position of the train is detected based on the transponder at the same time, but the train does not participate in the operation of the train. The position obtained based on the transponder is used to calculate a positioning error for training the neural network model. And after the training of the neural network model is finished, removing the crossed induction loop, and maintaining the normal running of the train by adopting the position obtained by the responder.
At this time, unlike the prior art in which error correction is performed only when the transponder passes through, in this embodiment, on the basis of the error correction, correction based on a neural network model is added to improve the number of times of correction, so that the positioning accuracy is improved as a whole without increasing more transponders.
The flow chart of the method provided by the embodiment of the invention is shown in fig. 2, and the embodiment improves an Automatic Train Operation (ATO) subsystem on a train and adds corresponding control logic and calculation logic. The method specifically comprises the following steps:
and S110, obtaining the position of the train based on the crossed induction loop, obtaining the position of the train based on the transponder, and maintaining the normal operation of the train only by adopting the position obtained by the crossed induction loop.
When the cross induction loop and the transponder coexist on the track, the vehicle-mounted ATP on the train obtains the position of the train through the cross induction loop and by combining a line database and vehicle-mounted speed measuring equipment; meanwhile, the vehicle-mounted ATP obtains the real-time position of the train through the vehicle-mounted speed measuring equipment, the position is corrected through the transponder, the position information of the transponder is fixed data in the line database, the data is accurate, and no error exists. The cross induction loop and the transponder are different in transmission system and can coexist independently.
And the vehicle-mounted computer calculates and adjusts the braking level to be applied by the train according to the position obtained by adopting the cross induction loop, the current train speed and the distance from the stopping point, so that the platform can be accurately stopped. Reference is made here in detail to the prior art, which is not described here in any further detail.
S120, recording the real position of each crossed induction loop crossing point through the vehicle-mounted ATP, and obtaining the non-real position of the train based on the vehicle-mounted speed measuring equipment and the transponder through the vehicle-mounted ATP; and calculating the positioning error of the vehicle-mounted ATP based on the vehicle-mounted speed measuring equipment and the transponder when each cross induction loop intersection point passes through according to the real position and the non-real position.
E.g., at time k, past one of the cross induction loop intersections m, the true position of intersection m is recorded. The position of the transponder is different from that of the intersection point, and the position obtained at the intersection point m based on the transponder and the vehicle-mounted speed measuring device contains accumulated errors and is called an unreal position. Then, a set of true and false positions is obtained when passing each intersection, so that the difference between the true and false positions yields a positioning error consistent with the number of intersections. Along with the increase of the running mileage and times of the train, a large number of positioning errors can be collected.
And S130, training a neural network model by taking the positioning error passing through each cross induction loop intersection as a label and the running data of the train as an input data sample.
The present embodiment mainly performs positioning correction on a new positioning device (i.e., a transponder), and needs to analyze the source of the positioning error. The main sources of positioning errors are the errors of the vehicle speed measuring equipment: counting error and wheel diameter wear. The counting error is mainly caused by wheel idle running and sliding; wheel diameter wear is the change in wheel diameter caused by wheel wear.
If the train idles, the running speed of the train is less than the wheel speed; if the train slides, the running speed of the train is higher than the wheel speed, so the difference between the real-time wheel speed and the train speed can represent the counting error of the train.
During train operation, the diameter will decrease continuously due to the continuous friction loss between the wheels and the track, so that the measured train operation distance is less than the actual operation distance. As the length of operation increases, an accumulative effect develops. Therefore, the total running time of the train can represent the error caused by the wheel diameter abrasion.
Referring to fig. 1, within a link distance, the positioning error increases as the distance increases, and thus the distance from the last transponder is also a factor.
Based on the analysis, recording the total running time of the train (calculated from the start of the train) when passing through each cross induction loop intersection; recording the accumulated value of the real-time wheel speed and the vehicle speed difference from each cross induction loop intersection to the last transponder; the mileage from each crossing induction loop crossing to the last transponder is recorded.
Fig. 3 is a schematic diagram of a transponder co-existing with a crossed induction loop, with transponders n and n +1 disposed across the intersection m of the crossed induction loop. Taking the train passing through the intersection m at the moment k as an example, recording the total running time of the train as 500 hours; recording the accumulated value of the real-time wheel speed and the vehicle speed difference between the cross point m and the last transponder n (the train actually runs from the last transponder n to the cross point m, and the backtracking calculation is carried out in the process); the mileage from the intersection m to the last transponder n is recorded.
And then, training a neural network model by taking the total running time, the accumulated value of the real-time wheel speed and the vehicle speed difference and the mileage as input data samples according to the positioning error passing each cross induction loop intersection as a label. The present embodiment does not limit the type of neural network. Preferably, a multi-input single-output BP neural network is used, which can be fitted to obtain a functional relationship between input and output.
S140, after the crossed induction loop is removed, maintaining normal running of the train by adopting the position obtained by the responder; and inputting the running data of the train into the neural network model to obtain the output positioning error.
Optionally, the current mileage at the current moment is obtained through the real position obtained based on the last transponder and the vehicle-mounted speed measuring device. Fig. 4 is a schematic diagram of positioning using a transponder according to an embodiment of the present invention. The real position is obtained when the vehicle-mounted speed measuring equipment passes through the transponder n, and the current mileage (counted from the position of the transponder n) is obtained after the vehicle-mounted speed measuring equipment passes through the transponder n. Then, the current running total time of the train, the accumulated value of the real-time wheel speed and the vehicle speed difference between the last transponder and the current moment and the current mileage are input into the neural network model to obtain the output positioning error.
Alternatively, the current time may be any time after the last transponder passes.
Preferably, since the positioning error in S120 is calculated at the intersection, the positioning error predicted by using the neural network model at the intersection is closer to the true error. Thus, the reference distance is defined as the distance between adjacent transponders and the intersection of crossing induction loops when new and old positioning devices coexist, see fig. 3.
Calculating the current mileage in real time, and if the difference between the current mileage and the reference distance is less than or equal to a set value (for example, 0.5 m), and the current position is considered to be the position of the previous intersection, executing the operation of inputting the current running total time length of the train, the accumulated value of the real-time wheel speed and the speed difference from the last transponder to the current moment, and the current mileage into the neural network model; and if the difference between the current mileage and the reference distance is larger than a set value, the current position is considered to not reach the position of the previous intersection, and the operation of obtaining the current mileage through the real position obtained based on the last transponder and the vehicle-mounted speed measuring equipment is returned to be executed.
And S150, compensating the position of the train obtained by the responder by adopting the output positioning error to obtain an updated positioning signal.
With continued reference to fig. 4, the position of the train is compensated at the current time to reduce the positioning error, and then compensated again when the next transponder is passed. The positioning error is significantly reduced compared to fig. 1 as a whole.
The method is suitable for a scene that new and old positioning equipment coexist during existing line signal disassembly, the old positioning equipment is a cross induction loop, the new positioning equipment is a transponder, the position of the train is obtained based on the cross induction loop, the position of the train is obtained based on the transponder, and the train is positioned only by adopting the cross induction loop during the train operation period, so that the normal operation of the train is ensured. Recording the real position of each crossed induction loop crossing point and the non-real position of the train obtained on the basis of the vehicle-mounted speed measuring equipment and the transponder; when the vehicle-mounted speed measuring device passes through the cross induction loop intersection, the real position can be obtained, but the vehicle-mounted speed measuring device does not pass through the transponder at the moment, and the non-real position (accumulated error with the real position) obtained by combining the position of the last transponder with the vehicle-mounted speed measuring device and the line database is still obtained.
And calculating the positioning error of the vehicle-mounted ATP based on the vehicle-mounted speed measuring equipment and the transponder when the vehicle-mounted ATP passes through each cross point of the cross induction loop according to the real position and the non-real position. Training a neural network model by taking a positioning error passing through each cross induction loop intersection as a label and taking the running data of the train as an input data sample; the neural network model represents the logic of the positioning error and operational data of the transponder as it passes through each intersection of the cross sense loops.
After the crossed induction loop is removed, positioning the train by adopting a transponder train during the running period; according to the positioning logic of the transponders, a real position can be obtained when the train passes through each transponder, but then a non-real position can be obtained by combining the vehicle-mounted speed measuring equipment and a line database, so that the running data of the train is input into the neural network model to obtain an output positioning error; the position of the train obtained by the responder is compensated by the outputted positioning error, so that the train can be compensated for once based on the cross induction loop before passing through the next responder, and when the train passes through the next responder, the train is compensated based on the real position of the next responder, so that the positioning precision can be integrally improved in the scene of positioning by the responder.
Finally, it should be noted that: the above embodiments are only used to illustrate the technical solution of the present invention, and not to limit the same; while the invention has been described in detail and with reference to the foregoing embodiments, it will be understood by those skilled in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some or all of the technical features may be equivalently replaced; and the modifications or the substitutions do not make the essence of the corresponding technical solutions deviate from the technical solutions of the embodiments of the present invention.
Claims (5)
1. An online updating method for urban rail transit signals is characterized by being applicable to scenes that new and old positioning equipment coexist when existing line signals are disassembled, wherein the old positioning equipment is a cross induction loop, and the new positioning equipment is a transponder;
the method comprises the following steps:
obtaining the position of the train based on the crossed induction loop, obtaining the position of the train based on the transponder, and maintaining the normal operation of the train only by adopting the position obtained by the crossed induction loop;
recording the real position of each crossed induction loop crossing point through the vehicle-mounted ATP, and obtaining the non-real position of the train based on the vehicle-mounted speed measuring equipment and the transponder by the vehicle-mounted ATP; the cross point of the cross induction loop is different from the setting position of the transponder; calculating the positioning error of the vehicle-mounted ATP based on the vehicle-mounted speed measuring equipment and the transponder when each cross induction loop intersection passes through according to the real position and the non-real position;
training a neural network model by taking the positioning error passing through each cross induction loop intersection as a label and the running data of the train as an input data sample;
after the crossed induction loop is removed, maintaining the normal running of the train by adopting the position obtained by the transponder; inputting the running data of the train to the neural network model to obtain an output positioning error;
and compensating the position of the train obtained by the responder by adopting the output positioning error to obtain an updated positioning signal.
2. The method of claim 1, wherein training a neural network model using the positioning error as a label when passing each crossing induction loop crossing and the train operation data as input data samples comprises:
recording the total running time of the train when the train passes through each cross induction loop intersection;
recording the accumulated value of the real-time wheel speed and the vehicle speed difference from each cross induction loop intersection to the last transponder;
recording the mileage from each cross induction loop intersection to the last transponder;
and training a neural network model by taking the total running time, the accumulated value of the real-time wheel speed and the vehicle speed difference and the mileage as input data samples according to the positioning error passing each cross induction loop intersection as a label.
3. The method of claim 1, wherein inputting operational data of the train to the neural network model, resulting in an output positioning error, comprises:
obtaining the current mileage at the current moment through the real position obtained based on the last transponder and the vehicle-mounted speed measuring equipment;
and inputting the current running total time of the train, the accumulated value of the real-time wheel speed and the vehicle speed difference between the last transponder and the current moment and the current mileage into the neural network model to obtain the output positioning error.
4. The method according to claim 3, wherein after obtaining the current mileage by the vehicle-mounted speed measuring device and the real position obtained based on the last transponder, the method further comprises:
if the difference between the current mileage and the reference distance is smaller than or equal to a set value, the operation of inputting the current running total time length of the train, the accumulated value of the real-time wheel speed and the speed difference from the last responder to the current moment and the current mileage into the neural network model is executed;
if the difference between the current mileage and the reference distance is larger than a set value, returning to execute the operation of obtaining the current mileage through the real position obtained based on the last responder and the vehicle-mounted speed measuring equipment;
and the reference distance is the distance between the adjacent transponders and the intersection points of the crossed induction loop lines when new positioning equipment and old positioning equipment coexist.
5. Method according to any of claims 1-4, characterized in that the transponder is arranged between two crossing points of crossing induction loops.
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| Title |
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| 蔡金山: "地铁移动闭塞信号系统车地通信传输技术研究", 《城市建筑》 * |
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| Publication number | Publication date |
|---|---|
| CN115071785B (en) | 2022-12-23 |
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