CN117850539A - Digital twinning-based time synchronization method, rail transit management method and system - Google Patents
Digital twinning-based time synchronization method, rail transit management method and system Download PDFInfo
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Abstract
The invention discloses a time synchronization method based on digital twinning, a rail transit management method and a rail transit management system, and relates to the field of information control. The invention includes, receive the information data packet; analyzing the time stamp, the equipment number and the information content contained in the information data packet; constructing a digital twin model according to the time stamp, the equipment number and the information content which are analyzed in the information data packets, wherein the information content contained in one or more information data packets constructs an event unit in the digital twin model; screening the same event unit in a digital twin model constructed by information content contained in a plurality of information data packets as a multi-mode crossing event unit; acquiring a plurality of time stamps corresponding to the multi-mode crossing event unit; and obtaining the actual occurrence time of the multi-modal cross event corresponding to the multi-modal cross event unit according to the plurality of time stamps corresponding to the multi-modal cross event unit. The invention realizes accurate time synchronization of a plurality of devices.
Description
Technical Field
The invention belongs to the technical field of information control, and particularly relates to a digital twinning-based time synchronization method, a rail transit management method and a system.
Background
With the rapid development of modern information technology, digital twin technology is gradually widely applied in various fields. Digital twinning means that a digital model corresponding to an entity in the real world is built in the virtual world, so that real-time monitoring, optimization and simulation of the entity are realized, and the management efficiency and the operation safety of the system are improved. In the field of rail traffic management, the digital twin technology has important application value, and can help to realize functions of real-time monitoring, fault diagnosis and prediction, intelligent scheduling and the like of rail traffic equipment and systems.
However, the various devices and components in a rail transit management system typically have complex timing relationships and require high time synchronization. How to realize accurate time synchronization so as to ensure efficient collaborative operation of all parts of the system becomes a problem to be solved urgently. The traditional time synchronization method generally depends on hardware clock and network communication, is easily affected by hardware faults, network delay and other factors, and cannot meet the high requirement of a rail transit management system on time synchronization precision.
The utility model discloses a time synchronization system and method based on track traffic, this system includes integrated monitoring system ISCS and industrial computer, integrated monitoring system passes through the ethernet with the industrial computer and connects, the industrial computer is equipped with HMI module, system clock and time server, HMI module is used for reading the data of PLC module, the PLC module is used for gathering the data of IO module and gives the HMI module, HMI module is used for obtaining the time letter of system clock and saves in data, and send this data to integrated monitoring system, integrated monitoring system is used for sending the time synchronization command to the industrial computer, time server is used for obtaining the time synchronization command that integrated monitoring system sent, and carry out data analysis, obtain time information, and control system clock modification time, the time information of system clock and integrated monitoring system's time information synchronization. The scheme relies on hardware network timing to realize time synchronization, and for track traffic with higher dispersity and complex environment, high-precision time synchronization is still difficult to maintain.
Disclosure of Invention
The invention aims to provide a time synchronization method based on digital twin, a rail transit management method and a system, which are used for analyzing data packets uploaded by scattered equipment so as to mine occurrence events at the same time and realize accurate time synchronization of a plurality of pieces of equipment.
In order to solve the technical problems, the invention is realized by the following technical scheme:
the invention provides a time synchronization method based on digital twin, which comprises the following steps of,
receiving an information data packet;
analyzing the time stamp, the equipment number and the information content contained in the information data packet;
constructing a digital twin model according to the time stamp, the equipment number and the information content which are analyzed in the information data packets, wherein the information content contained in one or more information data packets constructs an event unit in the digital twin model;
screening out the same event unit in the digital twin model constructed by the information content contained in a plurality of information data packets as a multi-mode crossing event unit;
acquiring a plurality of time stamps corresponding to the multi-mode crossing event unit;
obtaining the actual occurrence time of the multi-modal cross event corresponding to the multi-modal cross event unit according to a plurality of time stamps corresponding to the multi-modal cross event unit;
acquiring a plurality of equipment numbers corresponding to the multi-mode crossing event unit;
and carrying out time synchronization calibration on a plurality of devices corresponding to the multi-modal cross event unit according to the actual occurrence time of the multi-modal cross event corresponding to the multi-modal cross event unit.
In one embodiment of the present invention, the step of obtaining the actual occurrence time of the multi-modal cross event corresponding to the multi-modal cross event unit according to the plurality of time stamps corresponding to the multi-modal cross event unit includes,
acquiring distribution states of a plurality of time stamps corresponding to the multi-mode crossing event unit on a time axis;
screening out abnormal time stamps according to the distribution states of the time stamps on the time axis to obtain the distribution states of normal time stamps on the time axis;
acquiring an interval time period between each normal time stamp and an adjacent normal time stamp on a time axis;
acquiring the average value of the interval time periods of each normal time stamp and the adjacent normal time stamps as the interval average value time period of the normal time stamps;
acquiring the number of other normal time stamps of each normal time stamp on a time axis in a normal time stamp interval average time period before and after the normal time stamp as the time period density of the normal time stamp;
calculating to obtain the average value of the density of the time period where the normal time stamp is located;
and screening according to the density of the time period of the normal time stamp and the average value of the density of the time period of the normal time stamp to obtain the actual occurrence time of the multi-mode cross event corresponding to the multi-mode cross event unit.
In one embodiment of the present invention, the step of screening to obtain the actual occurrence time of the multi-modal cross event corresponding to the multi-modal cross event unit according to the density of the period of time of the normal timestamp and the average value of the density of the period of time of the normal timestamp includes,
arranging the density of the time intervals of each normal time stamp from high to low to obtain a normal time stamp density sequence;
selecting a normal time stamp density sequence according to the average value of the densities of the time periods of the normal time stamps to obtain a plurality of high-density normal time stamps;
judging whether the distribution span of a plurality of high-density normal time stamps on a time axis exceeds the average time period of two normal time stamp intervals or not;
if the time interval density is not exceeded, taking a normal time stamp with the highest time interval density in a normal time stamp density sequence as the actual occurrence time of the multi-mode cross event corresponding to the multi-mode cross event unit;
and if the device is in excess of the time-unreliable device, marking the device corresponding to the multi-mode crossing event unit as the time-unreliable device.
In one embodiment of the invention, the method further comprises,
judging whether the number or the proportion of the unreliable time devices exceeds a set value;
if not, not operating;
if yes, broadcasting and sending a synchronous calibration instruction containing a standard time stamp to all the devices, wherein the synchronous calibration instruction requires the receiving device to package the received time as the time stamp, the number of the receiving device and the received standard time stamp as information content into an information data packet to send.
In one embodiment of the invention, the method further comprises,
according to the corresponding relation between the information data packet and the multi-mode crossing event unit, obtaining the association relation between the information data packet and the actual occurrence time of the multi-mode crossing event;
screening out the actual occurrence time of a plurality of multi-mode crossing events corresponding to the same information data packet according to the association relation between the information data packet and the actual occurrence time of the multi-mode crossing events;
judging whether the actual occurrence moments of a plurality of multi-mode crossing events corresponding to the same information data packet are the same or not;
if the two types of the data are the same, not performing operation;
if the multiple multi-mode cross events are different, the actual occurrence time of the multiple multi-mode cross events corresponding to the same information data packet is taken as the time to be corrected;
acquiring a plurality of time stamps corresponding to each time to be corrected;
correcting the moment to be corrected according to a plurality of time stamps corresponding to each moment to be corrected, and obtaining the actual occurrence moment of the corrected multi-mode cross event;
and carrying out time synchronization calibration on the corresponding multiple devices according to the corrected actual occurrence time of the multi-mode cross event.
In one embodiment of the present invention, the step of correcting the time to be corrected according to the plurality of time stamps corresponding to each time to be corrected to obtain the actual occurrence time of the corrected multi-mode cross event includes,
acquiring the distribution state of the normal time stamp corresponding to each time to be corrected on a time axis;
obtaining the accuracy of each time to be corrected according to the distribution state of the normal time stamp corresponding to the time to be corrected on the time axis;
and taking the accuracy of the time to be corrected as the weight corresponding to the time to be corrected, and obtaining the weighted average of all the time to be corrected as the actual occurrence time of the corrected multi-mode cross event.
In one embodiment of the present invention, the step of obtaining the accuracy of each time to be corrected according to the distribution state of the normal time stamp corresponding to the time to be corrected on the time axis includes,
for each time instant to be corrected,
obtaining the number of all normal time stamps corresponding to the time to be corrected according to the distribution state of the normal time stamps corresponding to the time to be corrected on a time axis;
obtaining the normal time stamp with the highest density of the time interval of the normal time stamp corresponding to the time to be corrected on the time axis according to the distribution state of the normal time stamp corresponding to the time to be corrected on the time axis, wherein the normal time stamp is used as the leading normal time stamp of the time to be corrected in the average time interval of the normal time stamp on the time axis;
acquiring the number of the corresponding time stamps of the normal domain to be corrected;
and taking the ratio of the number of the corresponding generic normal time stamps to the number of all the corresponding normal time stamps to be corrected as the accuracy of the time to be corrected.
The invention also discloses a time synchronization method based on digital twin, which comprises the following steps,
transmitting the information data packet;
and receiving the time synchronization calibration.
The invention also discloses a track traffic management method based on digital twin,
receiving an information data packet;
analyzing a time stamp, a device number and information content contained in the information data packet, wherein the device comprises a train, and the information content comprises a train running state;
constructing a digital twin model according to the time stamp, the equipment number and the information content which are analyzed in the information data packets, wherein the information content contained in one or more information data packets constructs an event unit in the digital twin model, and the event unit comprises arrival information of a train;
screening out the same event unit in the digital twin model constructed by the information content contained in a plurality of information data packets as a multi-mode crossing event unit;
acquiring a plurality of time stamps corresponding to the multi-mode crossing event unit;
obtaining the actual occurrence time of the multi-modal cross event corresponding to the multi-modal cross event unit according to a plurality of time stamps corresponding to the multi-modal cross event unit;
acquiring a plurality of equipment numbers corresponding to the multi-mode crossing event unit;
and carrying out time synchronization calibration on a plurality of devices corresponding to the multi-modal cross event unit according to the actual occurrence time of the multi-modal cross event corresponding to the multi-modal cross event unit.
The invention also discloses a track traffic management system based on digital twinning, which comprises,
the device is used for sending information data packets, wherein the device comprises a train;
the main control end is used for receiving the information data packet;
analyzing a time stamp, a device number and information content contained in the information data packet, wherein the information content comprises a train running state;
constructing a digital twin model according to the time stamp, the equipment number and the information content which are analyzed in the information data packets, wherein the information content contained in one or more information data packets constructs an event unit in the digital twin model, and the event unit comprises arrival information of a train;
screening out the same event unit in the digital twin model constructed by the information content contained in a plurality of information data packets as a multi-mode crossing event unit;
acquiring a plurality of time stamps corresponding to the multi-mode crossing event unit;
obtaining the actual occurrence time of the multi-modal cross event corresponding to the multi-modal cross event unit according to a plurality of time stamps corresponding to the multi-modal cross event unit;
acquiring a plurality of equipment numbers corresponding to the multi-mode crossing event unit;
and carrying out time synchronization calibration on a plurality of devices corresponding to the multi-modal cross event unit according to the actual occurrence time of the multi-modal cross event corresponding to the multi-modal cross event unit.
The invention collects the information data packets uploaded by different devices, and further builds a digital twin model containing different events and corresponding time stamps. The digital twin model is analyzed to obtain the time difference of the same event occurrence record event time of different devices, the accurate actual time of the event occurrence can be obtained by analyzing based on the time difference, and the time synchronization is carried out on a plurality of related devices according to the accurate actual time.
Of course, it is not necessary for any one product to practice the invention to achieve all of the advantages set forth above at the same time.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings that are needed for the description of the embodiments will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and that other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
FIG. 1 is a schematic diagram of a digital twin-based time synchronization method according to the first embodiment of the present invention;
FIG. 2 is a schematic diagram of the steps in the step S6 of the present invention;
FIG. 3 is a schematic diagram showing a first step of the step S67 of the present invention;
FIG. 4 is a second schematic diagram of the step S67 of the present invention;
FIG. 5 is a schematic diagram showing the steps of a digital twin-based time synchronization method according to the present invention;
FIG. 6 is a schematic diagram of the steps in the step S15 of the present invention;
FIG. 7 is a schematic diagram illustrating the steps of the step S152 according to the present invention;
fig. 8 is a schematic diagram of functional modules and information flow of a digital twin-based rail transit management system according to the present invention.
In the drawings, the list of components represented by the various numbers is as follows:
1-master control end, 2-equipment and 21-train.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
Rail transit systems, particularly in underground rail transit systems, travel for a long time in the ground where wireless signals are difficult to penetrate, which makes it difficult to accurately control the running state of the train. However, rail transit is an important guarantee for social operation, and a train running in a tunnel may cause serious faults such as rear-end collision and the like due to untimely control under a high-load running state. In view of this, it is necessary to keep the equipment such as the train and the master in synchronization with accurate events.
In order to accurately control rail transit equipment such as trains, information data packets uploaded by various equipment are required to be collected in real time, and the information content in the information data packets is analyzed to construct a digital twin system for reflecting the overall running state of the rail transit system. However, the update confusion of the digital twin system can be caused by the untimely synchronization of the equipment and the information of the main control end, so that the practical application value is lost. In order to solve the above problems, the present invention provides the following.
Referring to fig. 1, the present invention provides a time synchronization method based on digital twinning, which may generally include two major parts of establishing a digital twinning model and analyzing the actual occurrence time of a multi-mode crossing event according to the digital twinning model. Step S1 may be executed to receive an information packet, where the packet may be sent by a device such as a vehicle directly through an intranet or through a public network. Step S2 may be performed to parse out the time stamp, the device number and the information content included in the information packet, and the data packet is encoded and packed according to a fixed format, so that the information packet is obtained by reverse compiling. Step S3 can be executed to construct a digital twin model according to the time stamp, the equipment number and the information content which are analyzed in the information data packet, wherein the digital twin model in the scheme is a virtual digital model for reflecting the running states of various equipment in the track traffic system, and mainly records the running events of the various equipment, so that in the digital twin model, the information content contained in one or more information data packets constructs an event unit in the digital twin model.
Step S4 may then be performed to filter out the same event unit in the digital twin model constructed from the information content contained in the plurality of information packets as a multi-modal cross event unit, i.e. the same event in which the plurality of devices participate. Step S5 may then be performed to obtain a plurality of time stamps corresponding to the multimodal cross event element, since the recording times of the different devices are different for the same event due to the local time differences of the different devices. Step S6 can be executed to obtain the actual occurrence time of the multi-mode crossing event corresponding to the multi-mode crossing event unit according to the plurality of time stamps corresponding to the multi-mode crossing event unit, and the actual occurrence time of the event can be analyzed by backward pushing different recording time of the same event, because the local time of a single device is affected by system hardware and has errors, but the overall expected value of the local event errors of a plurality of devices in the running process is consistent with the actual event. Step S7 may be performed to obtain a plurality of device numbers corresponding to the multimodal cross event element. And finally, executing step S8, and carrying out time synchronization calibration on a plurality of devices corresponding to the multi-modal cross event unit according to the actual occurrence time of the multi-modal cross event corresponding to the multi-modal cross event unit, namely analyzing the actual time through the twin digital model, and further carrying out time synchronization calibration on the devices.
Referring to fig. 2, after a long-time operation, the device may generate errors between the local time and the actual time due to processing errors of hardware, and these errors may be statistically described as probability-type events distributed normally, so that the actual time may be calculated by integrating the local times of a plurality of devices. In the implementation process, step S61 may be performed first to obtain distribution states of a plurality of timestamps corresponding to the multi-mode cross event unit on a time axis. Step S62 may be performed to screen out the abnormal time stamps according to the distribution states of the plurality of time stamps on the time axis, so as to obtain the distribution states of the normal time stamps on the time axis. Step S63 may be performed next to acquire an interval period of each normal time stamp and an adjacent normal time stamp on the time axis. Step S64 may be performed next to acquire the average value of the interval period of each normal time stamp and the adjacent normal time stamp as the normal time stamp interval average value period. Step S65 may be performed next to obtain the number of other normal time stamps in one normal time stamp interval mean time period before and after each normal time stamp on the time axis as the located time period density of the normal time stamps. Step S66 may then be performed to calculate the mean of the densities of the time periods in which the normal time stamps are located. And finally, step S67 can be executed to obtain the actual occurrence time of the multi-mode crossing event corresponding to the multi-mode crossing event unit according to the density of the time period of the normal time stamp and the average value of the density of the time period of the normal time stamp.
The scheme can be realized by the following program codes in actual implementation:
this code defines a series of functions for performing tasks in accordance with given steps. In the main function, the corresponding function is called according to the steps to process a plurality of time stamps corresponding to the multi-mode crossing event unit, and the actual occurrence time is screened out.
Referring to fig. 3, since the abnormal state of the timing module of the device may cause a large deviation of the local time of the device during the manufacturing process or during the operation process, in order to avoid adverse effects on the actual time of the subsequent calculation, the abnormal events need to be found and removed, so the step S67 may be executed first, and the step S671 may be executed to obtain a normal timestamp density sequence according to the density of the time period of each normal timestamp from high to low. Step S672 may be performed to select a normal timestamp density sequence according to the average value of the densities of the time periods of the normal timestamps to obtain a plurality of high-density normal timestamps. Step S673 may next be performed to determine whether the distribution span of the plurality of high-density normal timestamps on the time axis exceeds the two normal timestamp interval average time period. If not, step S674 may be executed next, where the normal timestamp with the highest period density in the normal timestamp density sequence is used as the actual occurrence time of the multi-mode crossing event corresponding to the multi-mode crossing event unit. If so, step S675 may be performed to mark the device corresponding to the multimodal cross event element as a time unreliable device.
The scheme can be realized by the following program codes in actual implementation:
this code example adds new functions to satisfy a given step based on previous implementations. Note that this code depends on functions in the previous example, such as remove_abnormal_ timestamps, calculate _ intervals, calculate _mean and calculate_density. Please ensure that these functions are used together in practical applications.
Referring to fig. 4, if there are too many unreliable time devices in the system, the system may malfunction, and the actual time generated in step S6 may be seriously lost, so that to avoid this situation, it needs to be determined whether the number or proportion of the unreliable time devices exceeds a set value, where the set value may be calculated according to the specific situation of the system, or may be set by the administrator, and generally, the set value does not exceed 5% of the total number of devices. If not, step S667 may be performed next without performing the operation. If yes, step S678 may be executed to broadcast a synchronous calibration command including a standard timestamp to all devices, where the synchronous calibration command requests the receiving device to package the received time as a timestamp, the number of the receiving device, and the received standard timestamp as information content into an information data packet for transmission. In this step, the event of the device responding to the synchronous calibration instruction is taken as a multi-modal cross event in a multi-modal cross event unit in the digital twin model, and the multi-modal cross event participated by all devices is also used for time synchronization of the whole devices through a standard time stamp.
Referring to fig. 5, the same device may participate in generating a plurality of multi-mode cross events, that is, the actual occurrence time of a plurality of multi-mode cross events corresponding to the same information packet, and if the actual occurrence time of a plurality of corresponding multi-mode cross events is inconsistent, it needs to be corrected, that is, after step S8 is executed, step S9 needs to be executed continuously, and the association relationship between the information packet and the actual occurrence time of the multi-mode cross event is obtained according to the correspondence between the information packet and the multi-mode cross event unit.
Step S10 can be executed to screen out the actual occurrence time of a plurality of multi-mode cross events corresponding to the same information data packet according to the association relation between the information data packet and the actual occurrence time of the multi-mode cross events. Step S11 may be performed to determine whether the actual occurrence times of the multiple multi-mode cross events corresponding to the same information packet are the same. If the information packets are the same, step S12 may be executed next, and if the information packets are not the same, step S13 may be executed next to take the actual occurrence time of the multiple multi-mode cross events corresponding to the same information packet as the time to be corrected. Step S14 may be performed to obtain a plurality of time stamps corresponding to each time to be corrected. Step S15 may be executed to correct the time to be corrected according to the plurality of time stamps corresponding to each time to be corrected, so as to obtain the corrected actual occurrence time of the multi-mode cross event. Finally, step S16 may be executed to perform time synchronization calibration on the corresponding multiple devices according to the corrected actual occurrence time of the multimodal cross event.
The scheme can be realized by the following program codes in actual implementation:
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this code example defines a series of functions for performing tasks in accordance with given steps. In the main function, the corresponding functions are called according to the steps to process the corresponding relation between the information data packet and the multi-mode crossing event unit and perform time synchronization calibration.
Referring to fig. 6 and 7, in order to correct the actual occurrence time of the multi-modal crossover event, reference needs to be made to a plurality of normal timestamps that generate the actual occurrence time of the multi-modal crossover event, so step S151 needs to be performed first to obtain the distribution state of the normal timestamp corresponding to each time to be corrected on the time axis. Step S152 may be executed to obtain the accuracy of each time to be corrected according to the distribution state of the normal timestamp corresponding to the time to be corrected on the time axis. And finally, step S153 may be executed to take the accuracy of the time to be corrected as the weight corresponding to the time to be corrected, and obtain the weighted average of all the time to be corrected as the actual occurrence time of the corrected multi-mode cross event. However, in step S1521, since there are various statistical analysis manners for generating the plurality of normal timestamps of the actual occurrence time of the multi-modal cross event, in order to implement the correction function for the actual occurrence time of the multi-modal cross event, it is necessary to refer to the valid normal timestamps thereof, that is, for each time to be corrected, step S1521 may be executed first to obtain the number of all the normal timestamps corresponding to the time to be corrected according to the distribution state of the normal timestamps corresponding to the time to be corrected on the time axis. Step S1522 may be executed to obtain, according to the distribution state of the normal time stamp corresponding to the time to be corrected on the time axis, the normal time stamp with the highest time interval density corresponding to the time to be corrected, where the normal time stamp is located, on the time axis, in a time interval average time period of one front and one back normal time stamps, where the normal time stamp is located, as the lead normal time stamp of the time to be corrected. Step S1523 may be performed to obtain the number of the generic normal time stamps corresponding to the time to be corrected. Finally, step S1524 may be executed to take the ratio of the number of the corresponding generic normal time stamps to the number of all the corresponding normal time stamps to be corrected as the accuracy of the time to be corrected.
The scheme can be realized by the following program codes in actual implementation:
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this code example defines a series of functions for performing tasks in accordance with given steps. In the main function, the corresponding function is called according to the steps to process the accuracy of the moment to be corrected. Note that this code depends on some of the variables and functions in the previous example, such as adjusted_ timestamps, normal _timetables and mean_interval. Ensuring that these variables are used with the function in practice.
The whole steps are the working flow of the whole system from the view angle of the control end, and the view angle analysis of the equipment mainly comprises two steps, namely, sending information data packets, and receiving time synchronization calibration. Other implementation details are not described in detail.
In particular to a track traffic system, the scheme also discloses a track traffic management method based on digital twinning, and in the implementation process, the step S1 can be executed to receive the information data packet. Step S2 may be performed to parse out the timestamp, the device number, and the information content included in the information packet, where the device includes a train, and the information content includes a train running state. Step S3 can be executed to construct a digital twin model according to the time stamp, the equipment number and the information content which are analyzed in the information data packets, wherein the information content contained in one or more information data packets constructs an event unit in the digital twin model, and the event unit comprises arrival information of a train. Step S4 may then be performed to filter out the same event unit within the digital twin model constructed from the information content contained in the plurality of information data packets as a multi-modal crossover event unit. Step S5 may be performed to obtain a plurality of time stamps corresponding to the multi-modal crossing event unit. Step S6 may be executed to obtain the actual occurrence time of the multi-modal cross event corresponding to the multi-modal cross event unit according to the plurality of time stamps corresponding to the multi-modal cross event unit. Step S7 may be performed to obtain a plurality of device numbers corresponding to the multimodal cross event element. And finally, executing step S8 to perform time synchronization calibration on the plurality of devices corresponding to the multi-modal cross event unit according to the actual occurrence time of the multi-modal cross event corresponding to the multi-modal cross event unit. The digital twin model is obtained by virtually modeling the events participated by the equipment such as the train in the rail transit system, the model is analyzed to obtain the local time of the equipment such as the train participated in the same thing, the actual time is obtained through analysis, the time synchronization calibration is carried out on the equipment such as the train according to the actual time, and the out-of-control caused by the time synchronization in the running process of the rail transit system is avoided.
Next, the scheme combines the master control terminal 1 and the equipment 2 for specific analysis.
Referring to fig. 8, the present solution also discloses a digital twin-based rail traffic management system, which is functionally divided, and may include a master control terminal 1 and a device 2. The master control terminal 1 may be a master control server of a rail transit system, and is configured to receive and transmit various data and commands, and may also store various data. The device 2 may be a train 21, a gate, a screen door, a broadcasting device, a light control device, or the like. The device 2 is arranged to transmit information data packets. The master control terminal 1 may first execute step S1 to receive the information data packet during the operation. Step S2 may be performed to parse out the timestamp, the equipment number, and the information content included in the information packet, where the information content includes the train running status. Step S3 can be executed to construct a digital twin model according to the time stamp, the equipment number and the information content which are analyzed in the information data packets, wherein the information content contained in one or more information data packets constructs an event unit in the digital twin model, and the event unit comprises arrival information of a train. Step S4 may then be performed to filter out the same event unit within the digital twin model constructed from the information content contained in the plurality of information data packets as a multi-modal crossover event unit. Step S5 may be performed to obtain a plurality of time stamps corresponding to the multi-modal crossing event unit. Step S6 may be executed to obtain the actual occurrence time of the multi-modal cross event corresponding to the multi-modal cross event unit according to the plurality of time stamps corresponding to the multi-modal cross event unit. Step S7 may be performed to obtain a plurality of device numbers corresponding to the multimodal cross event element. And finally, executing step S8 to perform time synchronization calibration on the plurality of devices corresponding to the multi-modal cross event unit according to the actual occurrence time of the multi-modal cross event corresponding to the multi-modal cross event unit. The specific operation principle can be seen from the above part, and the time synchronization of the equipment is realized through the construction and analysis of a digital twin model, so that the operation fault of the rail transit system caused by time errors is effectively avoided.
In summary, in the implementation process of the scheme, the digital twin model is constructed by receiving the information data packet and analyzing the content of the data packet. And acquiring a time stamp and a device number by using the multi-mode cross event unit in the model, and performing time synchronization calibration on the device. By constructing and analyzing the digital twin model, the time synchronization of a plurality of different-place devices in the system is realized, and the reliability of the rail transit system is improved.
The above description of illustrated embodiments of the invention, including what is described in the abstract, is not intended to be exhaustive or to limit the invention to the precise forms disclosed herein. Although specific embodiments of, and examples for, the invention are described herein for illustrative purposes only, various equivalent modifications are possible within the spirit and scope of the present invention, as those skilled in the relevant art will recognize and appreciate. As noted, these modifications can be made to the present invention in light of the foregoing description of illustrated embodiments of the present invention and are to be included within the spirit and scope of the present invention.
The systems and methods have been described herein in general terms as being helpful in understanding the details of the present invention. Furthermore, various specific details have been set forth in order to provide a thorough understanding of embodiments of the invention. One skilled in the relevant art will recognize, however, that an embodiment of the invention can be practiced without one or more of the specific details, or with other apparatus, systems, assemblies, methods, components, materials, parts, and/or the like. In other instances, well-known structures, materials, and/or operations are not specifically shown or described in detail to avoid obscuring aspects of embodiments of the invention.
Thus, although the invention has been described herein with reference to particular embodiments thereof, a latitude of modification, various changes and substitutions are intended in the foregoing disclosures, and it will be appreciated that in some instances some features of the invention will be employed without a corresponding use of other features without departing from the scope and spirit of the invention as set forth. Therefore, many modifications may be made to adapt a particular situation or material to the essential scope and spirit of the present invention. It is intended that the invention not be limited to the particular terms used in following claims and/or to the particular embodiment disclosed as the best mode contemplated for carrying out this invention, but that the invention will include any and all embodiments and equivalents falling within the scope of the appended claims. Accordingly, the scope of the invention should be determined only by the following claims.
Claims (10)
1. A time synchronization method based on digital twinning is characterized by comprising the following steps of,
receiving an information data packet;
analyzing the time stamp, the equipment number and the information content contained in the information data packet;
constructing a digital twin model according to the time stamp, the equipment number and the information content which are analyzed in the information data packets, wherein the information content contained in one or more information data packets constructs an event unit in the digital twin model;
screening out the same event unit in the digital twin model constructed by the information content contained in a plurality of information data packets as a multi-mode crossing event unit;
acquiring a plurality of time stamps corresponding to the multi-mode crossing event unit;
obtaining the actual occurrence time of the multi-modal cross event corresponding to the multi-modal cross event unit according to a plurality of time stamps corresponding to the multi-modal cross event unit;
acquiring a plurality of equipment numbers corresponding to the multi-mode crossing event unit;
and carrying out time synchronization calibration on a plurality of devices corresponding to the multi-modal cross event unit according to the actual occurrence time of the multi-modal cross event corresponding to the multi-modal cross event unit.
2. The method of claim 1, wherein the step of obtaining the actual occurrence time of the multi-modal crossover event corresponding to the multi-modal crossover event unit from the plurality of time stamps corresponding to the multi-modal crossover event unit comprises,
acquiring distribution states of a plurality of time stamps corresponding to the multi-mode crossing event unit on a time axis;
screening out abnormal time stamps according to the distribution states of the time stamps on the time axis to obtain the distribution states of normal time stamps on the time axis;
acquiring an interval time period between each normal time stamp and an adjacent normal time stamp on a time axis;
acquiring the average value of the interval time periods of each normal time stamp and the adjacent normal time stamps as the interval average value time period of the normal time stamps;
acquiring the number of other normal time stamps of each normal time stamp on a time axis in a normal time stamp interval average time period before and after the normal time stamp as the time period density of the normal time stamp;
calculating to obtain the average value of the density of the time period where the normal time stamp is located;
and screening according to the density of the time period of the normal time stamp and the average value of the density of the time period of the normal time stamp to obtain the actual occurrence time of the multi-mode cross event corresponding to the multi-mode cross event unit.
3. The method according to claim 2, wherein the step of obtaining the actual occurrence time of the multi-modal cross event corresponding to the multi-modal cross event unit by screening according to the density of the time periods of the normal time stamp and the average value of the density of the time periods of the normal time stamp comprises,
arranging the density of the time intervals of each normal time stamp from high to low to obtain a normal time stamp density sequence;
selecting a normal time stamp density sequence according to the average value of the densities of the time periods of the normal time stamps to obtain a plurality of high-density normal time stamps;
judging whether the distribution span of a plurality of high-density normal time stamps on a time axis exceeds the average time period of two normal time stamp intervals or not;
if the time interval density is not exceeded, taking a normal time stamp with the highest time interval density in a normal time stamp density sequence as the actual occurrence time of the multi-mode cross event corresponding to the multi-mode cross event unit;
and if the device is in excess of the time-unreliable device, marking the device corresponding to the multi-mode crossing event unit as the time-unreliable device.
4. The method of claim 1, further comprising,
judging whether the number or the proportion of the unreliable time devices exceeds a set value;
if not, not operating;
if yes, broadcasting and sending a synchronous calibration instruction containing a standard time stamp to all the devices, wherein the synchronous calibration instruction requires the receiving device to package the received time as the time stamp, the number of the receiving device and the received standard time stamp as information content into an information data packet to send.
5. The method of claim 1, further comprising,
according to the corresponding relation between the information data packet and the multi-mode crossing event unit, obtaining the association relation between the information data packet and the actual occurrence time of the multi-mode crossing event;
screening out the actual occurrence time of a plurality of multi-mode crossing events corresponding to the same information data packet according to the association relation between the information data packet and the actual occurrence time of the multi-mode crossing events;
judging whether the actual occurrence moments of a plurality of multi-mode crossing events corresponding to the same information data packet are the same or not;
if the two types of the data are the same, not performing operation;
if the multiple multi-mode cross events are different, the actual occurrence time of the multiple multi-mode cross events corresponding to the same information data packet is taken as the time to be corrected;
acquiring a plurality of time stamps corresponding to each time to be corrected;
correcting the moment to be corrected according to a plurality of time stamps corresponding to each moment to be corrected, and obtaining the actual occurrence moment of the corrected multi-mode cross event;
and carrying out time synchronization calibration on the corresponding multiple devices according to the corrected actual occurrence time of the multi-mode cross event.
6. The method of claim 5, wherein the step of correcting the time to be corrected according to the plurality of time stamps corresponding to each time to be corrected to obtain the actual occurrence time of the corrected multi-modal crossover event comprises,
acquiring the distribution state of the normal time stamp corresponding to each time to be corrected on a time axis;
obtaining the accuracy of each time to be corrected according to the distribution state of the normal time stamp corresponding to the time to be corrected on the time axis;
and taking the accuracy of the time to be corrected as the weight corresponding to the time to be corrected, and obtaining the weighted average of all the time to be corrected as the actual occurrence time of the corrected multi-mode cross event.
7. The method of claim 6, wherein the step of obtaining the accuracy of each time to be corrected based on the distribution of the normal time stamps corresponding to the time to be corrected on the time axis comprises,
for each time instant to be corrected,
obtaining the number of all normal time stamps corresponding to the time to be corrected according to the distribution state of the normal time stamps corresponding to the time to be corrected on a time axis;
obtaining the normal time stamp with the highest density of the time interval of the normal time stamp corresponding to the time to be corrected on the time axis according to the distribution state of the normal time stamp corresponding to the time to be corrected on the time axis, wherein the normal time stamp is used as the leading normal time stamp of the time to be corrected in the average time interval of the normal time stamp on the time axis;
acquiring the number of the corresponding time stamps of the normal domain to be corrected;
and taking the ratio of the number of the corresponding generic normal time stamps to the number of all the corresponding normal time stamps to be corrected as the accuracy of the time to be corrected.
8. A time synchronization method based on digital twinning is characterized by comprising the following steps of,
transmitting an information data packet according to any one of claims 1 to 7;
receiving a time-synchronized calibration of any one of claims 1 to 7.
9. A rail transit management method based on digital twinning is characterized in that,
receiving an information data packet;
analyzing a time stamp, a device number and information content contained in the information data packet, wherein the device comprises a train, and the information content comprises a train running state;
constructing a digital twin model according to the time stamp, the equipment number and the information content which are analyzed in the information data packets, wherein the information content contained in one or more information data packets constructs an event unit in the digital twin model, and the event unit comprises arrival information of a train;
screening out the same event unit in the digital twin model constructed by the information content contained in a plurality of information data packets as a multi-mode crossing event unit;
acquiring a plurality of time stamps corresponding to the multi-mode crossing event unit;
obtaining the actual occurrence time of the multi-modal cross event corresponding to the multi-modal cross event unit according to a plurality of time stamps corresponding to the multi-modal cross event unit;
acquiring a plurality of equipment numbers corresponding to the multi-mode crossing event unit;
and carrying out time synchronization calibration on a plurality of devices corresponding to the multi-modal cross event unit according to the actual occurrence time of the multi-modal cross event corresponding to the multi-modal cross event unit.
10. A digital twinning-based rail traffic management system is characterized by comprising,
the device is used for sending information data packets, wherein the device comprises a train;
the main control end is used for receiving the information data packet;
analyzing a time stamp, a device number and information content contained in the information data packet, wherein the information content comprises a train running state;
constructing a digital twin model according to the time stamp, the equipment number and the information content which are analyzed in the information data packets, wherein the information content contained in one or more information data packets constructs an event unit in the digital twin model, and the event unit comprises arrival information of a train;
screening out the same event unit in the digital twin model constructed by the information content contained in a plurality of information data packets as a multi-mode crossing event unit;
acquiring a plurality of time stamps corresponding to the multi-mode crossing event unit;
obtaining the actual occurrence time of the multi-modal cross event corresponding to the multi-modal cross event unit according to a plurality of time stamps corresponding to the multi-modal cross event unit;
acquiring a plurality of equipment numbers corresponding to the multi-mode crossing event unit;
and carrying out time synchronization calibration on a plurality of devices corresponding to the multi-modal cross event unit according to the actual occurrence time of the multi-modal cross event corresponding to the multi-modal cross event unit.
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