CN114996264A - Data processing method, device and equipment for digital twins - Google Patents
Data processing method, device and equipment for digital twins Download PDFInfo
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L47/00—Traffic control in data switching networks
- H04L47/10—Flow control; Congestion control
- H04L47/28—Flow control; Congestion control in relation to timing considerations
- H04L47/283—Flow control; Congestion control in relation to timing considerations in response to processing delays, e.g. caused by jitter or round trip time [RTT]
Abstract
The application discloses a data processing method facing digital twins, which comprises the following steps: acquiring a plurality of existing continuous state information parameters, constructing a state information prediction model according to the existing continuous state information parameters, and acquiring predicted state information through the state information prediction model; carrying out threshold filtering on the prediction state information by a similarity algorithm to obtain optimal prediction state information; constructing a state information fusion model according to the optimal prediction state information, and acquiring fusion state information through the state information fusion model; constructing a state information aggregation model according to the predicted state information, the optimal predicted state information and the fusion state information, and obtaining aggregation state information through the state information aggregation model; and sending the aggregation state information to the twin end.
Description
Technical Field
The present application relates to the field of data processing technologies, and in particular, to a data processing method, apparatus, and device for digital twinning.
Background
The complexity of traffic conditions rises linearly, the automatic driving technology rises, and the service range and the technical level of the Internet of vehicles are also known more highly and more recently. The accuracy requirement of running visual tracking is higher and higher for traffic participants taking networked vehicles as main bodies, and in order to achieve visual and accurate locking of running state information of the traffic participants, the industry provides a digital twin technology to meet the visual requirement of the internet of vehicles service.
The existing 'digital twin' technology adopts a state information buffer mechanism in order to better express and restore the state information process of participants, so that the authenticity of the state information is sacrificed.
Disclosure of Invention
The embodiment of the specification provides a data processing method, a data processing device and data processing equipment for digital twins, which are used for solving the problems that the double image phenomenon in the twins process is caused by the multi-source state information caused by the diversity of the state information extraction technology in the prior art and the state information is lost under the condition of a signal blind area.
The embodiment of the specification adopts the following technical scheme:
in a first aspect, an embodiment of the present specification provides a data processing method facing a digital twin, where the method includes:
acquiring a plurality of existing continuous state information parameters, constructing a state information prediction model according to the existing continuous state information parameters, and acquiring predicted state information through the state information prediction model;
carrying out threshold filtering on the prediction state information by a similarity algorithm to obtain optimal prediction state information;
constructing a state information fusion model according to the optimal prediction state information, and acquiring fusion state information through the state information fusion model;
constructing a state information aggregation model according to the predicted state information, the optimal predicted state information and the fusion state information, and obtaining aggregation state information through the state information aggregation model;
and sending the polymerization state information to a twin end, wherein the twin end is a device for mapping the state information of the target object.
In a second aspect, embodiments of the present specification further provide a data processing method facing a digital twin, where the method includes:
acquiring a starting time stamp and an ending time stamp of the received aggregation state information;
setting a slice amount between the start timestamp and the end timestamp;
acquiring an aggregation state information data parameter of the aggregation state information;
carrying out equal slicing on the aggregation state information data parameters according to the slice amount, and outputting an aggregation state information sequence;
and sending the aggregation state information sequence to a user interface.
In a third aspect, embodiments of the present specification further provide a digital twin-oriented data processing apparatus, including:
the prediction model module is used for acquiring a plurality of existing continuous state information parameters, constructing a state information prediction model according to the existing continuous state information parameters, and acquiring prediction state information through the state information prediction model;
the filtering module is used for carrying out threshold filtering on the prediction state information by a similarity algorithm to obtain optimal prediction state information;
the fusion model module is used for constructing a state information fusion model according to the optimal prediction state information and acquiring fusion state information through the state information fusion model;
the aggregation model module is used for constructing a state information aggregation model according to the prediction state information, the optimal prediction state information and the fusion state information, and acquiring aggregation state information through the state information aggregation model;
and the communication module is used for sending the aggregation state information to a twin end, and the twin end is equipment used for mapping the state information of the target object.
In a fourth aspect, embodiments of the present specification further provide a digital twin-oriented data processing apparatus, including:
the collecting module is used for obtaining a starting time stamp and an ending time stamp for receiving the aggregation state information;
a setting module for setting the slice amount between the start timestamp and the end timestamp;
the extraction module is used for acquiring the aggregation state information data parameters;
the slicing module is used for carrying out equal slicing on the aggregation state information data parameters according to the slice amount and outputting an aggregation state information sequence;
and the conveying module is used for sending the aggregation state information sequence to a user interface.
In a fifth aspect, this specification further provides an electronic device, including at least one processor and a memory, where the memory stores a program and is configured to enable the at least one processor to execute the digital twin oriented data processing method in this specification.
The embodiment of the specification adopts at least one technical scheme which can achieve the following beneficial effects: by constructing a state information prediction model, the aim of predicting the state information of the signal blind area is fulfilled, and the continuity of the twin state information is improved; and the purpose of carrying out state information aggregation on the multi-source state information is achieved through the constructed state information aggregation model.
Drawings
The accompanying drawings, which are included to provide a further understanding of the embodiments of the specification and are incorporated in and constitute a part of this specification, illustrate exemplary embodiments of the specification and together with the description serve to explain the application and not to limit the application. In the drawings:
fig. 1 is a schematic flowchart of a digital twin oriented data processing method provided in an embodiment of the present disclosure;
fig. 2 is a schematic flowchart of a method for sending the aggregation state information to a twin end in a digital twin-oriented data processing method provided by an embodiment of the present specification;
fig. 3 is a schematic flow chart of a data transmission method in a digital twin-oriented data processing method according to an embodiment of the present disclosure;
fig. 4 is a schematic structural diagram of a digital twin oriented data processing apparatus provided in an embodiment of the present specification;
FIG. 5 is a schematic flow chart of a digital twin oriented data processing method provided in an embodiment of the present disclosure;
fig. 6 is a schematic structural diagram of a data processing apparatus facing a digital twin according to an embodiment of the present disclosure.
Detailed Description
The concept of the internet of vehicles is derived from the internet of things, namely the internet of vehicles, the internet of vehicles is characterized in that vehicles in driving are used as information perception objects, network connection between vehicles and X (namely vehicles, people, roads and service platforms) is realized by means of a new generation of information communication technology, the integral intelligent driving level of the vehicles is improved, safe, comfortable, intelligent and efficient driving feeling and traffic service are provided for users, meanwhile, the traffic operation efficiency is improved, and the intelligent level of social traffic service is improved.
The car networking realizes the all-round network link of car and cloud platform, car and car, car and road, car and people, car interior through the information communication technology of new generation, has mainly realized "three nets merge", namely fuses car intranet, intercar network and on-vehicle mobile internet. The internet of vehicles senses the state information of vehicles by using a sensing technology, and realizes intelligent management of traffic, intelligent decision of traffic information service and intelligent control of vehicles by using a wireless communication network and a modern intelligent information processing technology.
The intelligent network connection is based on the development of the traditional vehicle networking, as the traffic working conditions become more and more complex, the traditional traffic regulation and optimization means have reached the bottleneck, the traffic can be regulated, optimized and the safety guarantee can be improved only by the intelligent network connection technology, and as the intelligent network connection is a set of traffic AI technology which is established based on IT technology and is subjected to rule analysis and model optimization, a process which needs to be known and accepted is inevitably generated in the development process, so that the requirement of vividly and visually expressing the maturity of the intelligent network connection capability becomes relatively urgent in the initial stage of application or the stable guarantee period, and the digital generation becomes a powerful technical means for the requirement.
The traffic conditions are complicated and changeable, and besides, the shapes, colors and various situations of participants also provide higher requirements for quality assurance of digital twins, so that the operation situations of the individual participants in the traffic conditions can be timely and accurately fed back, the intelligent capacity output effect based on the driving optimization can be expressed, and various technical architectures of service indexes such as state information time delay, entity models, capacity models, state information processes and the like are provided for the industry.
The basic purpose of the prior art is to establish the technical processing delay requirements of all the layers depending on the twin, lack a necessary compensation mechanism for the occurring state information delay, and adopt a state information buffering mechanism in order to better express and restore the state information process of the participants, thereby actually sacrificing the authenticity of the state information, which is as follows.
The prior art does not consider the discontinuity problem of the state information twin process caused by the signal blind zone of the state information process zone; the prior art does not consider the state information multiple sources caused by the diversity of the participant state information extraction technology, thereby causing the ghost phenomenon in the twin process; the state information buffering mechanism provided by the prior art causes the state information delay to finally sacrifice the real-time property and the authenticity of the state information; the prior art has low extraction frequency of the state information, and does not provide an optimization scheme for the problem of unsmooth twin effect caused by state information dispersion.
Therefore, the embodiment of the specification provides a data processing method and device for a digital twin and an electronic device, and the purpose of predicting the state information of a signal blind area is achieved by constructing a state information prediction model, so that the continuity of the state information twin is improved; the purpose of carrying out state information aggregation on the multi-source state information is achieved through the constructed state information aggregation model; the problem of state information distortion is solved through state information compensation; and the twin smoothing effect of the state information is improved through the state information slicing.
In order to make the objects, technical solutions and advantages of the present application more clear, the technical solutions of the present application will be clearly and completely described below with reference to the specific embodiments of the present specification and the accompanying drawings. It is to be understood that the embodiments described are only a few embodiments of the present disclosure, and not all embodiments. All other embodiments obtained by a person skilled in the art based on the embodiments in the present specification without any inventive step are within the scope of the present application.
Example 1
Fig. 1 is a schematic flow chart of a data processing method facing digital twinning provided in an embodiment of the specification.
Referring to fig. 1, embodiment 1 provides a data processing method for digital twinning, which can be applied to a platform side, and the method includes the following steps:
s101, obtaining a plurality of existing continuous state information parameters, constructing a state information prediction model according to the existing continuous state information parameters, and obtaining predicted state information through the state information prediction model;
in particular, the status information may be understood as operating status information. The existing continuous status information can be understood as already known operating status information. The method for constructing the state information prediction model includes, but is not limited to, obtaining continuous time corresponding to a plurality of the existing continuous state information parameters; and constructing a state information prediction model by using a plurality of existing continuous state information parameters and continuous time based on a fitting algorithm.
The manner of obtaining the predicted state information according to the state information prediction model includes, but is not limited to, constructing a weight state information parameter sequence according to a plurality of the existing continuous state information parameters; inputting the weighted state information parameter sequence into the state information prediction model to obtain a fitting state information coefficient; acquiring a prediction state information time period, and dividing the prediction state information time period into a plurality of prediction state information time slices; generating a predicted state information parameter sequence according to the fitting state information coefficient and the predicted state information time slice; constructing a predicted state information sequence based on the predicted state information parameter sequence; and acquiring the prediction state information from the prediction state information sequence. The operating state information can be understood as traffic environment operating state information, moving object operating state information, and fixed object operating state information. As another example, the moving object operating state information includes, but is not limited to, people, animals, birds, and vehicles moving on the road.
As an application example, the state information prediction model may adopt the following expression:
wherein:
Q j (x) Setting polynomial order n as a basis function to obtain a curve polynomial function, inputting a point sequence to be fitted (i.e. a state information sequence to be fitted in the present scheme) to the curve polynomial function, so that the total error value function is satisfied, and obtaining a polynomial coefficient
(i.e., the state information coefficients to be fitted).
Acquiring a predicted state information time period, and dividing the predicted state information time period into a plurality of predicted state information time slices, for example, the predicted state information time period is 1s, and the predicted state information time slice is one (200ms (millisecond)) and can be divided into five predicted state information time slices;
acquiring continuous state information N, N-1, N-2;
construction of weight State information sequence [ (1, 0, X) n )、(1，1000，X n-1 )、(1，2000，X n-2 )]Inputting the data into a polynomial state information curve fitting algorithm; obtaining fitting state information coefficient (PX) n ，PX n+1 ，PX n+2 )；
And constructing predicted state information (Xn +1, Xn +2, Xn +3, Xn +4 and Xn +5) based on the fitting state information coefficients and the predicted state information time slices.
It should be understood that the above-mentioned details are for illustrative purposes only and should not be construed as limiting the present application in any way.
S103, performing threshold filtering on the prediction state information through a similarity algorithm to obtain optimal prediction state information;
specifically, the filtering manner includes, but is not limited to, filtering the predicted state information using kalman filtering. And performing Kalman filtering on the predicted state information to obtain optimal predicted state information. It can also be understood that the optimum predicted state information X 'corresponding to the predicted time is obtained' n+1 。
As an application example, assuming that the last state information is k, the current prediction state information is constructed according to the system model (formula 1, formula 2):
x (k | k-1) ═ A X (k-1| k-1) + B U (k) (equation 1)
Remarking: x (k | k-1) is the last state information prediction result, X (k-1| k-1) is the last state information optimum result, and U (k) is the current state information control quantity, which may be 0 if there is no control quantity.
P (k | k-1) ═ A P (k-1| k-1) a' + Q (equation 2)
Remarking: p (k | k-1) is the covariance of X (k | k-1), P (k-1| k-1) is the covariance of X (k-1| k-1), A' represents the transpose of A, and Q is the covariance of the system process.
With the current state information prediction results, the current state information measurements are collected. Combining the predicted value and the measured value to obtain an optimized estimated value X (k | k) of the current state information (k) through (formula 3, formula 4):
x (k | k) ═ X (k | k-1) + kg (k) (z (k) -H X (k | k-1)) (formula 3)
Where Kg is Kalman Gain (Kalman Gain):
kg (k) ═ P (k | k-1) H '/(H P (k | k-1) H' + R) (formula 4)
Through the optimal estimated value X (k | k) under the k state information and the continuous running of the Kalman filter (formula 5) until the system process is finished, the optimal predicted state information X 'after the final filtering of the current state information is obtained' n+1 ：
P (k | k) ═ (I-kg (k) H) P (k | k-1) (formula 5)
Remarking: where I is a matrix of 1, I ═ 1 for single model single measurements. When the system enters the k +1 state information, P (k | k) is P (k-1| k-1) of equation (2).
It should be understood that the above-mentioned details are for illustrative purposes only and should not be construed as limiting the present application in any way.
S105, constructing a state information fusion model according to the optimal prediction state information, and obtaining fusion state information through the state information fusion model;
specifically, the state information fusion model may use the following expression:
Y n+1 ＝X′ n+1 P n+1 +X′ (n+1)2 P n+1
wherein, X' n+1 Is the optimal predicted state information after threshold filtering by a similarity algorithm, P n+1 Represents the optimal predicted State information X' n+1 Covariance matrix of (Y) n+1 Is the fusion status information.
It should be understood that the above-listed details are for illustrative purposes only and should not be construed as limiting the present invention in any way.
S107, constructing a state information aggregation model according to the predicted state information, the optimal predicted state information and the fusion state information, and obtaining the aggregation state information through the state information aggregation model;
specifically, the status information aggregation model may use the following expression:
Z n+1 ＝X n+1 +Y n+1 -\′ n+1
wherein, X n+1 Is predicted status information, X' n+1 Is the optimal predicted state information after threshold filtering by a similarity algorithm, P n+1 Represents the optimal predicted State information X' n+1 Covariance matrix of (Y) n+1 To fuse state information, Z n+1 And the final aggregation state information is obtained after data compensation processing is carried out on the fusion state information.
As an application example, the collection status information is inputThe sequence is as follows: x n1 、X n2 、X nn Obtaining a time-aligned prediction state information sequence in a state information prediction model: x (n+1)1 、X (n+1)2 、X (n+1)n 。
Obtaining an optimal prediction state information sequence X 'after threshold filtering is carried out on the prediction state information sequence by a similarity calculation method' (n+1)1 、X′ (n+1)2 、X′ (n+1)n 。
Inputting optimal prediction state information sequence X' n+1 Obtaining the fusion state information Y by a fusion equation of the state information n+1 ；
Input fusion status information Y n+1 Obtaining the aggregation state information Z by a state information aggregation model n+1 。
It should be understood that the above-mentioned details are for illustrative purposes only and should not be construed as limiting the present application in any way.
And S109, sending the aggregation state information to a twin end, wherein the twin end is equipment for mapping the state information of the target object.
Specifically, the transmission mode to the twin end may be a common mode, such as directly mapping the aggregation state information to the twin end.
According to the embodiment of the disclosure, the prediction state information can be obtained through the state information prediction model by constructing the state information prediction model; and predicting the state information of the signal blind area, solving the problem of discontinuous state information caused by the state information blind area and improving the continuity of the state information.
Obtaining optimal prediction state information by performing threshold filtering on the prediction state information through a similarity algorithm; constructing a state information fusion model according to the optimal prediction state information, and acquiring fusion state information through the state information fusion model; constructing a state information aggregation model according to the predicted state information, the optimal predicted state information and the fusion state information, and obtaining aggregation state information through the state information aggregation model; and sending the aggregation state information to the twin end. The purpose of condensing multi-source state information into single state information is achieved, and the function of clearly displaying the target state information at the twin end is achieved.
In order to better implement the embodiment, the target state information is predicted in advance through the constructed state information prediction model to perform state information compensation, so that the problem of state information distortion caused by a state information compensation mechanism is solved, and the authenticity of state information twins is improved.
Specifically, a compensation state information time period is obtained, and the compensation state information time period is divided into a plurality of compensation state information time slices; generating a weight state information sequence according to a plurality of compensation state information time slices; inputting the weight state information sequence into the state information prediction model to obtain a fitting state information coefficient; and generating compensation state information according to the fitting state information coefficient and the compensation state information time slice. The manner of acquiring the compensation status information is substantially the same as that of acquiring the prediction status information, and the description thereof will not be repeated.
Furthermore, in the prior art, the extraction period of the state information is millisecond-level, so that the twin effect caused by the dispersion of the state information is not smooth. To this end, please refer to fig. 2, where fig. 2 is a schematic flowchart of a method for sending the aggregation state information to a twin end in a digital twin-oriented data processing method according to an embodiment of the specification. The method comprises the following steps:
s201, acquiring a starting time stamp and an ending time stamp of the aggregation state information;
specifically, the start timestamp may be understood as the time when the platform first sends the aggregation state information to the twin end; the end timestamp may be understood as the time when the platform last sent the aggregation state information to the twin. And each piece of sent aggregation state information corresponds to a timestamp, and the timestamp corresponding to the starting state information and the timestamp corresponding to the ending state information are obtained.
It should be understood that the above-mentioned details are for illustrative purposes only and should not be construed as limiting the present application in any way.
S203, setting the slice amount between the starting time stamp and the ending time stamp;
specifically, the state information frequency is input, and the slice amount from the start state information timestamp to the end state information timestamp is acquired.
It should be understood that the above-mentioned details are for illustrative purposes only and should not be construed as limiting the present application in any way.
S205, acquiring an aggregation state information data parameter of the aggregation state information;
specifically, the aggregation status information data parameters include, but are not limited to: GPS or heading angle or speed or timestamp.
It should be understood that the above-mentioned details are for illustrative purposes only and should not be construed as limiting the present application in any way.
S207, equally slicing the aggregation state information data parameters according to the slice amount, and outputting an aggregation state information sequence;
specifically, the uniform slicing of the aggregation state information data parameters according to the slice amount may be understood as performing uniform slicing on the GPS, the course angle, the speed, and the timestamp in the aggregation state information data parameters according to the slice amount.
It should be understood that the above-mentioned details are for illustrative purposes only and should not be construed as limiting the present application in any way.
S209, sending the aggregation state information sequence to a twin end.
The embodiment of the disclosure can improve the smoothness of the twin of the state information by slicing the sent aggregation state information data parameters.
Further, in the prior art, delay jitter is easily caused due to the dependence on the communication delay of each technical layer. Therefore, please refer to fig. 3, wherein fig. 3 is a schematic flow chart of a data transmission method in a data processing method facing a digital twin according to an embodiment of the specification. The method comprises the following steps:
s301, judging whether the aggregation state information is sent to the twin end and overflows or not, if so, judging whether the overflow amount of the overflow exceeds a set overflow valve slot, and if so, backing up communication state information, wherein the overflow valve slot refers to the overflow amount which can be processed within the overflow duration;
specifically, overflow may be understood as data overflowing a channel during channel transmission, and overflow traffic may be understood as data overflowing the channel.
In one embodiment, a high level (overflow valve slot 80%) and a low level (overflow valve slot 20%) of overflow traffic are set, overflow is flagged and backed up when communication status information exceeds the high level, and an overflow timestamp is recorded.
And S303, starting new communication state information to transmit the backup communication state information, wherein the new communication state information and old communication state information run synchronously, and the old communication state information refers to the communication state information which transmits the aggregation state information to the twin end.
Specifically, a switching time stamp of the overflow valve slot is set; the overflow time may be understood as the time when the overflow flow reaches a threshold value. And setting the reference time of the new communication state information as an overflow time stamp, and stopping the old communication state information when the overflow time stamp of the new communication state information exceeds the switching time stamp of the overflow valve slot to complete the switching of the communication state information.
According to the embodiment of the disclosure, whether the overflow amount exceeds the set overflow amount can be judged through the set overflow valve slot, if the overflow amount exceeds the set overflow amount, new communication state information is started to output flow, and the state information is recovered from the state information backup in the last step by setting the reference time of the new communication state information as the overflow timestamp, the new communication state information and the old communication state information run synchronously, and when the new communication state information timestamp exceeds the current time, the old communication state information is stopped, and the purpose of switching the communication state information is finally completed. The purpose of reducing the flow loss in stable data transmission is achieved.
Further, please refer to fig. 4, where fig. 4 is a schematic structural diagram of a data processing apparatus facing a digital twin according to an embodiment of the present disclosure. The device comprises:
the prediction model module 401 is configured to obtain a plurality of existing continuous state information parameters, construct a state information prediction model according to the plurality of existing continuous state information parameters, and obtain predicted state information through the state information prediction model.
And a filtering module 403, configured to perform threshold filtering on the prediction state information through a similarity algorithm to obtain optimal prediction state information.
And a fusion model module 405, configured to construct a state information fusion model according to the optimal predicted state information, and obtain fusion state information through the state information fusion model.
The aggregation model module 407 is configured to construct a state information aggregation model according to the predicted state information, the optimal predicted state information, and the fusion state information, and obtain aggregation state information through the state information aggregation model.
A communication module 409, configured to send the aggregation state information to a twin end, where the twin end is a device for mapping state information of a target object.
The data acquisition module is used for acquiring a plurality of continuous state information parameters; and the continuous time acquisition unit is also used for acquiring continuous time corresponding to a plurality of continuous state information parameters.
And the model construction module is used for constructing a state information prediction model by using a plurality of continuous state information parameters and continuous time based on a fitting algorithm.
And the sequence construction module is used for constructing a weight state information parameter sequence according to the continuous state information.
And the calculation module is used for inputting the weight state information parameter sequence into the state information prediction model to obtain a fitting state information coefficient.
The data acquisition module is further configured to acquire a predicted state information time period and divide the predicted state information time period into a plurality of predicted state information time slices.
The sequence construction module is also used for generating a predicted state information parameter sequence according to the fitting state information coefficient and the predicted state information time slice; and constructing a predicted state information sequence based on the predicted state information parameter sequence.
The judging module is used for judging whether the aggregation state information is sent to the twin end and overflows or not, if so, judging whether the overflow amount of the overflow exceeds a set overflow valve slot or not, and if so, backing up the communication state information, wherein the overflow valve slot refers to the overflow amount which can be processed within the overflow duration;
and the communication module is used for starting new communication state information to transmit the backup communication state information, the new communication state information and old communication state information run synchronously, and the old communication state information refers to the communication state information which sends the aggregation state information to the twin end.
Further, an electronic device is provided, which includes at least one processor and a memory, the memory storing a program and being configured such that the at least one processor performs the digital twin oriented data processing method of the embodiment.
Further, a computer-readable storage medium is provided, which stores computer instructions for causing the computer to execute a digital twin oriented data processing method of the embodiment.
Example 2
Referring to fig. 5, fig. 5 is a schematic flow chart of a data processing method for digital twinning provided in an embodiment of the specification, and embodiment 2 provides a data processing method for digital twinning, which is applied to a twinning end, and the method includes:
s501, acquiring a starting time stamp and an ending time stamp of the received aggregation state information;
specifically, the start timestamp may be understood as the time when the twin end first receives the aggregation state information; the end timestamp may be understood as the time when the twin end last received the aggregation state information. And each piece of received aggregation state information corresponds to a timestamp, and the timestamp corresponding to the starting state information and the timestamp corresponding to the ending state information are obtained.
It should be understood that the above-mentioned details are for illustrative purposes only and should not be construed as limiting the present application in any way.
S503, setting the slice amount between the starting time stamp and the ending time stamp;
specifically, the state information frequency is input, and the slice amount from the start state information timestamp to the end state information timestamp is acquired.
It should be understood that the above-mentioned details are for illustrative purposes only and should not be construed as limiting the present application in any way.
S505, acquiring an aggregation state information data parameter of the aggregation state information;
specifically, the aggregation status information data parameters include, but are not limited to: GPS or heading angle or speed or time stamp.
It should be understood that the above-mentioned details are for illustrative purposes only and should not be construed as limiting the present application in any way.
S507, carrying out equal slicing on the data parameters of the aggregation state information according to the slice amount, and outputting an aggregation state information sequence;
specifically, the uniform slicing is performed on the aggregation state information data parameter according to the slice amount, which may be understood as performing uniform slicing on the state information parameter GPS, the heading angle, the speed, and the timestamp according to the slice amount, and outputting the aggregation state information sequence.
It should be understood that the above-mentioned details are for illustrative purposes only and should not be construed as limiting the present application in any way.
S509, the aggregation state information sequence is sent to a user interface.
According to the embodiment of the disclosure, by slicing the data parameters of the sent aggregation state information, the smoothness of the twin of the state information can be improved, and the twin effect is improved.
Further, referring to fig. 6, fig. 6 is a data processing apparatus facing to digital twinning provided in the embodiment of the specification, where the apparatus includes:
an acquisition module 601, configured to acquire a start timestamp and an end timestamp of receiving aggregation state information;
a setting module 602, configured to set a slice amount between the start timestamp and the end timestamp;
an extracting module 603, configured to obtain aggregation state information data parameters;
a slicing module 604, configured to perform equal slicing on the aggregation state information data parameters according to the slice amount, and output an aggregation state information sequence;
a delivering module 605, configured to send the aggregation state information sequence to a user interface.
In the 90 s of the 20 th century, improvements in a technology could clearly distinguish between improvements in hardware (e.g., improvements in circuit structures such as diodes, transistors, switches, etc.) and improvements in software (improvements in process flow). However, as technology advances, many of today's process flow improvements have been seen as direct improvements in hardware circuit architecture. Designers almost always obtain the corresponding hardware circuit structure by programming an improved method flow into the hardware circuit. Thus, it cannot be said that an improvement in the process flow cannot be realized by hardware physical modules. For example, a Programmable Logic Device (PLD), such as a Field Programmable Gate Array (FPGA), is an integrated circuit whose Logic functions are determined by programming the Device by a user. A digital system is "integrated" on a PLD by the designer's own programming without requiring the chip manufacturer to design and fabricate application-specific integrated circuit chips. Furthermore, nowadays, instead of manually making an integrated Circuit chip, such Programming is often implemented by "logic compiler" software, which is similar to a software compiler used in program development and writing, but the original code before compiling is also written by a specific Programming Language, which is called Hardware Description Language (HDL), and HDL is not only one but many, such as abel (advanced Boolean Expression Language), ahdl (alternate Language Description Language), traffic, pl (core unified Programming Language), HDCal, JHDL (Java Hardware Description Language), langue, Lola, HDL, laspam, hardsradware (Hardware Description Language), vhjhd (Hardware Description Language), and vhigh-Language, which are currently used in most common. It will also be apparent to those skilled in the art that hardware circuitry that implements the logical method flows can be readily obtained by merely slightly programming the method flows into an integrated circuit using the hardware description languages described above.
The controller may be implemented in any suitable manner, for example, the controller may take the form of, for example, a microprocessor or processor and a computer-readable medium storing computer-readable program code (e.g., software or firmware) executable by the (micro) processor, logic gates, switches, an Application Specific Integrated Circuit (ASIC), a programmable logic controller, and an embedded microcontroller, examples of which include, but are not limited to, the following microcontrollers: ARC 625D, Atmel AT91SAM, Microchip PIC18F26K20, and Silicone Labs C8051F320, the memory controller may also be implemented as part of the control logic of the memory. Those skilled in the art will also appreciate that, in addition to implementing the controller as pure computer readable program code, the same functionality can be implemented by logically programming method steps such that the controller is in the form of logic gates, switches, application specific integrated circuits, programmable logic controllers, embedded microcontrollers and the like. Such a controller may thus be considered a hardware component, and the means included therein for performing the various functions may also be considered as a structure within the hardware component. Or even means for performing the functions may be regarded as being both a software module for performing the method and a structure within a hardware component.
The systems, devices, modules or units illustrated in the above-described embodiments may be implemented by a computer chip or an entity, or by a product with certain functions. One typical implementation is a computer. In particular, the computer may be, for example, a personal computer, a laptop computer, a cellular telephone, a camera phone, a smartphone, a personal digital assistant, a media player, a navigation device, an email device, a game console, a tablet computer, a wearable device, or a combination of any of these devices.
For convenience of description, the above devices are described as being divided into various modules or units by function, respectively. Of course, the functionality of the modules or units may be implemented in the same one or more software and/or hardware when implementing the present application.
As will be appreciated by one skilled in the art, embodiments of the present invention may be provided as a method, system, or computer program product. Accordingly, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present invention may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The present invention is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the specification. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process flow such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
In a typical configuration, a computing device includes one or more processors (CPUs), input/output interfaces, network interfaces, and memory.
The memory may include forms of volatile memory in a computer readable medium, Random Access Memory (RAM) and/or non-volatile memory (NVM), such as Read Only Memory (ROM) or flash memory (flash RAM). Memory is an example of a computer-readable medium.
Computer-readable media, including both non-transitory and non-transitory, removable and non-removable media, may implement information storage by any method or technology. The information may be computer readable instructions, data structures, modules of a program, or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), Static Random Access Memory (SRAM), Dynamic Random Access Memory (DRAM), other types of Random Access Memory (RAM), Read Only Memory (ROM), Electrically Erasable Programmable Read Only Memory (EEPROM), flash memory or other memory technology, compact disc read only memory (CD-ROM), Digital Versatile Discs (DVD) or other optical storage, magnetic cassettes, magnetic tape magnetic disk storage or other magnetic storage devices, or any other non-transmission medium that can be used to store information that can be accessed by a computing device. As defined herein, a computer readable medium does not include a transitory computer readable medium such as a modulated data signal and a carrier wave.
It should also be noted that the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other identical elements in the process, method, article, or apparatus that comprises the element.
The application may be described in the general context of computer-executable instructions, such as program modules, being executed by a computer. Generally, program modules include routines, programs, objects, components, data structures, etc. that perform particular tasks or implement particular abstract data types. The application may also be practiced in distributed computing environments where tasks are performed by remote processing devices that are linked through a communications network. In a distributed computing environment, program modules may be located in both local and remote computer storage media including memory storage devices.
The embodiments in the present specification are described in a progressive manner, and the same and similar parts among the embodiments are referred to each other, and each embodiment focuses on the differences from the other embodiments. In particular, for the system embodiment, since it is substantially similar to the method embodiment, the description is simple, and for the relevant points, reference may be made to the partial description of the method embodiment.
The above description is only an illustrative example of the present application and is not intended to limit the present application. Various modifications and changes may occur to those skilled in the art. Any modification, equivalent replacement, improvement or the like made within the spirit and principle of the present application shall be included in the scope of the claims of the present application.
Claims (10)
1. A digital twinning oriented data processing method, the method comprising:
acquiring a plurality of existing continuous state information parameters of a target object, constructing a state information prediction model according to the existing continuous state information parameters, and acquiring predicted state information of the target object through the state information prediction model;
carrying out threshold filtering on the prediction state information by a similarity algorithm to obtain optimal prediction state information;
constructing a state information fusion model according to the optimal prediction state information, and acquiring fusion state information through the state information fusion model;
constructing a state information aggregation model according to the predicted state information, the optimal predicted state information and the fusion state information, and obtaining aggregation state information through the state information aggregation model;
and sending the polymerization state information to a twin end, wherein the twin end is a device for mapping the state information of the target object.
2. The digital twin-oriented data processing method according to claim 1, wherein the building of the state information prediction model includes:
acquiring continuous time corresponding to a plurality of existing continuous state information parameters;
and constructing a state information prediction model by using a plurality of existing continuous state information parameters and the continuous time based on a fitting algorithm.
3. The digital twin-oriented data processing method as claimed in claim 2, wherein said obtaining predicted state information by said state information prediction model comprises:
constructing a weight state information parameter sequence according to a plurality of the existing continuous state information parameters;
inputting the weighted state information parameter sequence into the state information prediction model to obtain a fitting state information coefficient;
acquiring a prediction state information time period, and dividing the prediction state information time period into a plurality of prediction state information time slices;
generating a predicted state information parameter sequence according to the fitting state information coefficient and the predicted state information time slice;
constructing a predicted state information sequence based on the predicted state information parameter sequence;
and acquiring the prediction state information from the prediction state information sequence.
4. The data processing method facing the digital twin as claimed in claim 1, wherein after sending the aggregation state information to the twin end, the method further comprises:
judging whether the aggregation state information is sent to the twin end to overflow or not, if so, judging whether the overflow amount of the overflow exceeds a set overflow valve slot, and if so, backing up the communication state information, wherein the overflow valve slot refers to the overflow amount which can be processed within the overflow duration;
and starting new communication state information to transmit the backup communication state information, wherein the new communication state information and old communication state information run synchronously, and the old communication state information refers to the communication state information for sending the aggregation state information to the twin end.
5. The digital twin oriented data processing method of claim 4, wherein the backing up communication state information further comprises: an overflow timestamp is recorded.
6. The digital twin-oriented data processing method as claimed in claim 5, further comprising after the new communication state information and the old communication state information are synchronously operated:
setting a switching time stamp of the overflow valve slot;
and setting the reference time of the new communication state information as an overflow time stamp, and stopping the old communication state information when the overflow time stamp of the new communication state information exceeds the switching time stamp of the overflow valve slot to complete the switching of the communication state information.
7. A digital twin oriented data processing method, the method comprising:
acquiring a starting time stamp and an ending time stamp of the received aggregation state information;
setting a slice volume between the start timestamp and the end timestamp;
acquiring an aggregation state information data parameter of the aggregation state information;
carrying out equal slicing on the aggregation state information data parameters according to the slice amount, and outputting an aggregation state information sequence;
and sending the aggregation state information sequence to a user interface.
8. A digital twinning oriented data processing apparatus, comprising:
the prediction model module is used for acquiring a plurality of existing continuous state information parameters, constructing a state information prediction model according to the existing continuous state information parameters, and acquiring prediction state information through the state information prediction model;
the filtering module is used for carrying out threshold filtering on the prediction state information by a similarity algorithm to obtain optimal prediction state information;
the fusion model module is used for constructing a state information fusion model according to the optimal prediction state information and acquiring fusion state information through the state information fusion model;
the aggregation model module is used for constructing a state information aggregation model according to the prediction state information, the optimal prediction state information and the fusion state information, and acquiring aggregation state information through the state information aggregation model;
and the communication module is used for sending the aggregation state information to a twin end, and the twin end is equipment for mapping the state information of the target object.
9. A digital twin oriented data processing apparatus comprising:
the collecting module is used for obtaining a starting time stamp and an ending time stamp for receiving the aggregation state information;
a setting module for setting the slice amount between the start timestamp and the end timestamp;
the extraction module is used for acquiring the aggregation state information data parameters;
the slicing module is used for carrying out equal slicing on the aggregation state information data parameters according to the slice amount and outputting an aggregation state information sequence;
and the conveying module is used for sending the aggregation state information sequence to a user interface.
10. An electronic device comprising at least one processor and a memory, the memory storing a program and configured to the at least one processor to perform a digital twin oriented data processing method as claimed in any one of claims 1-7.
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| CN116151155A (en) * | 2023-04-19 | 2023-05-23 | 南昌工程学院 | Digital twinning-based urban combined overflow system flow monitoring method and system |
| CN116151155B (en) * | 2023-04-19 | 2023-08-04 | 南昌工程学院 | Digital twinning-based urban combined overflow system flow monitoring method and system |
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