CN113569321A - Road tunnel running state simulation method based on digital twin model - Google Patents
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Abstract
The invention discloses a road tunnel running state simulation method based on a digital twin model, which comprises the following steps: firstly, constructing a tunnel virtual scene of a highway tunnel according to corresponding civil engineering structure data; then, collecting real-time data of physical equipment in the highway tunnel for data processing to obtain state data reflecting the state of the physical equipment and scene characteristic quantity data reflecting the running state of the tunnel; then, predicting the maintenance time of corresponding physical equipment through state data, and creating a corresponding digital twin model in the tunnel virtual scene according to the scene characteristic quantity data, wherein the digital twin model carries out model evolution along with the change of the scene characteristic quantity data; and finally, judging whether the maintenance time of the physical equipment is reached, and in response to the reaching of the maintenance time, re-creating a corresponding digital twin model in the tunnel virtual scene according to the scene characteristic quantity data. The running state in the tunnel is intuitively and really reflected in real time through the digital twin model.
Description
Technical Field
The invention relates to the technical field of 3D modeling of computer graphics, in particular to a road tunnel running state simulation method based on a digital twin model.
Background
In the road tunnel safety operation work, the actual operation conditions in the tunnel are particularly important, the potential safety hazards of the tunnel can be reflected at the first time, and the safety state of the tunnel is often measured by using the conditions. However, most of the prior art still stays at a monitoring data display level, which cannot intuitively reflect the actual operation condition of the tunnel and cannot truly reflect the operation state in the tunnel. Therefore, there is a need for a technology that can intuitively and truly reflect the operating conditions in the tunnel.
Disclosure of Invention
Aiming at the defects in the prior art, the invention provides a road tunnel operation state simulation method based on a digital twin model, which can truly and intuitively reflect the real-time operation state in a tunnel.
In a first aspect, a road tunnel operation state simulation method based on a digital twin model is provided, which includes:
constructing a tunnel virtual scene of the highway tunnel according to the corresponding civil structure data;
acquiring real-time data of physical equipment in a highway tunnel to perform data processing to obtain state data reflecting the state of the physical equipment and scene characteristic quantity data reflecting the running state of the tunnel;
predicting the maintenance time of corresponding physical equipment through state data, and creating a corresponding digital twin model in the tunnel virtual scene according to scene characteristic quantity data, wherein the digital twin model carries out model evolution along with the change of the scene characteristic quantity data;
and judging whether the maintenance time of the physical equipment is reached, and in response to the reaching of the maintenance time, creating a corresponding digital twin model in the tunnel virtual scene according to the scene characteristic quantity data again.
With reference to the first aspect, in a first implementable manner of the first aspect, the constructing the tunnel virtual scene includes:
dividing the tunnel into a plurality of section tunnels according to the civil structure data of the highway tunnel, and determining the civil structure data and the connection points of each section tunnel;
constructing a connection three-dimensional model of each section of tunnel through corresponding civil engineering structure data, and determining connection point coordinates among the sections of tunnels;
and connecting the three-dimensional model of each section of tunnel according to the coordinates of the connecting points to obtain a tunnel virtual scene.
With reference to the first implementable manner of the first aspect, in a second implementable manner of the first aspect, the constructing the joined three-dimensional model includes:
respectively creating three-dimensional coordinate systems perpendicular to the route at the head-tail connection positions of the section tunnels;
based on a three-dimensional coordinate system, constructing a structural outline of the sectional tunnel according to civil engineering structure data, and determining the coordinates of the joint points of the sectional tunnel;
constructing a three-dimensional model of the sectional tunnel according to the corresponding structural outline and the route;
creating a solid three-dimensional model of the segmental tunnel based on the corresponding three-dimensional model;
and carrying out Boolean difference set operation on the solid three-dimensional model of each section tunnel according to the coordinates of the joint points to obtain a corresponding joint three-dimensional model.
With reference to the first implementable manner of the first aspect, in a third implementable manner of the first aspect, the method further includes:
packaging the jointed three-dimensional model of the section tunnel into a jointed three-dimensional assembly;
selecting corresponding connection three-dimensional components of tunnels of all sections, and connecting according to connection point coordinates to form the tunnel virtual scene.
With reference to the first aspect, in a fourth implementable manner of the first aspect, the processing the real-time data includes: and carrying out noise reduction, abnormal value elimination and missing data compensation on the real-time data.
With reference to the first aspect, in a fifth implementable manner of the first aspect, the predicting a maintenance time of the physical device includes:
determining the current degradation state of the physical equipment according to the state data;
determining a state measurement value when the corresponding test equipment is in the degradation state and fault time when the test equipment fails;
calculating a similarity parameter between the physical equipment and the test equipment according to the state data and the state measured value;
predicting the maintenance time of the physical equipment according to the similarity parameter and the failure time;
and correcting the maintenance time of the physical equipment through a confidence function theory.
With reference to the first aspect, in a sixth implementable manner of the first aspect, creating a corresponding digital twin model in a tunnel virtual scene includes:
constructing digital twin models in different forms according to scene characteristic quantity data of physical equipment;
defining a data interface between digital twin models with different forms and scene characteristic quantity data of physical equipment;
and acquiring real-time scene characteristic quantity data of the physical equipment, and matching the digital twin model with a corresponding form through a data interface to assemble the digital twin model into a tunnel virtual scene.
With reference to the sixth implementable manner of the first aspect, in a seventh implementable manner of the first aspect, the method further includes:
defining a data interface between digital twin models of different forms and state data of physical equipment;
and acquiring real-time state data of the physical equipment, and matching the digital twin model with a corresponding form through a data interface to assemble the digital twin model into a tunnel virtual scene.
In a second aspect, a storage medium is provided, which stores a computer program, and when the computer program runs, the method for simulating the running state of the road tunnel based on the digital twin model according to any one of the first aspect and the first to the seventh implementation manners of the first aspect is executed.
Has the advantages that: by adopting the road tunnel running state simulation method based on the digital twin model, real running states of tunnel equipment, traffic, environment and the like are analyzed, a real-time data mapping matching model of a tunnel virtual scene and physical equipment in a tunnel is established, and real-time digital mapping of the digital twin model in the tunnel virtual scene and an actual running scene in the tunnel is realized, so that the running state in the tunnel is intuitively and really reflected in real time.
Drawings
In order to more clearly illustrate the embodiments of the present invention, the drawings, which are required to be used in the embodiments, will be briefly described below. In all the drawings, the elements or parts are not necessarily drawn to actual scale.
FIG. 1 is a flow chart of a simulation method according to an embodiment of the present invention;
FIG. 2 is a flow chart for constructing a tunnel virtual scene;
FIG. 3 is a flow chart of building a joined three-dimensional model of a segmental tunnel
FIG. 4 is a flow chart of predicting a maintenance time of a physical device.
Detailed Description
Embodiments of the present invention will be described in detail below with reference to the accompanying drawings. The following examples are only for illustrating the technical solutions of the present invention more clearly, and therefore are only examples, and the protection scope of the present invention is not limited thereby.
Fig. 1 is a flow chart of a road tunnel operation state simulation method based on a digital twin model, and the simulation method comprises the following steps:
step 1, constructing a tunnel virtual scene of a road tunnel according to corresponding civil engineering structure data;
step 2, collecting real-time data of physical equipment in the highway tunnel to perform data processing, and obtaining state data reflecting the state of the physical equipment and scene characteristic quantity data reflecting the running state of the tunnel;
step 3, predicting the maintenance time of corresponding physical equipment through state data, and creating a corresponding digital twin model in the tunnel virtual scene according to the scene characteristic quantity data, wherein the digital twin model carries out model evolution along with the change of the scene characteristic quantity data;
and 4, judging whether the maintenance time of the physical equipment is reached, and in response to the reaching of the maintenance time, re-creating a corresponding digital twin model in the tunnel virtual scene according to the scene characteristic quantity data. Specifically, the method comprises the following steps:
firstly, a tunnel virtual scene can be constructed in a display platform for displaying the running state of the tunnel according to the civil structure data of the road tunnel, wherein the civil structure data can be a two-dimensional plan view of the road tunnel.
Then, the display platform can be in communication connection with physical equipment in the highway tunnel through the Internet of things, and monitoring data in the tunnel and running state data of the equipment can be collected in real time through the physical equipment. For example, traffic information is monitored by a microwave vehicle inspection device, luminance value data is monitored by a luminance detector, and carbon monoxide concentration and visibility in a tunnel are monitored by a CO/VI detector. The display platform can process the real-time data so as to obtain state data reflecting the running state of the physical equipment, and the monitoring data are processed so as to obtain scene characteristic quantity data reflecting the running state in the tunnel.
Then, the display platform can create a corresponding virtual three-dimensional model according to the scene characteristic quantity data, for example, a full-type vehicle three-dimensional model is built through the scene characteristic quantity data of the microwave vehicle detector, a multi-weather scene three-dimensional model is built according to the scene characteristic quantity data of the brightness detector, and a multi-form smoke three-dimensional model is built according to the scene characteristic quantity data of the CO/VI detector. By defining data interfaces between these virtual three-dimensional models and scene feature quantity data of the respective physical devices, digital twin models of the respective physical devices can be constructed. Therefore, after the display platform collects real-time monitoring data, corresponding real-time scene characteristic quantity data can be obtained through data processing, the corresponding virtual three-dimensional models are matched through the data interfaces, the matched virtual three-dimensional models are assembled to the tunnel virtual scene, a real-time data mapping matching model of the tunnel virtual scene and physical equipment in the tunnel is established, real-time digital mapping of a digital twin model in the tunnel virtual scene and an actual operation scene in the tunnel is achieved, and therefore the operation state in the tunnel is visually and really reflected in real time.
In addition, the display platform can predict the maintenance time of the physical equipment through real-time state data, namely the time when the physical equipment fails. The display platform can judge whether the physical equipment needs to be maintained or not through the maintenance time, and if not, the display platform can not update the digital twin model corresponding to the physical equipment. If the physical equipment needs to be maintained, the display platform can reconstruct a corresponding digital twin model through the monitored data of the maintained physical equipment after the maintenance is finished, so that the influence caused by the change of the monitored data after the equipment is maintained and replaced is reduced, and the running state in the tunnel is truly reflected.
In this embodiment, preferably, as shown in fig. 2, constructing the tunnel virtual scene includes:
1-1, dividing a tunnel into a plurality of section tunnels according to civil structure data of a highway tunnel, and determining the civil structure data and a connection point of each section tunnel;
step 1-2, constructing a connection three-dimensional model of each section of tunnel through corresponding civil engineering structure data, and determining connection point coordinates among the sections of tunnels;
and 1-3, connecting the three-dimensional model of each section of tunnel according to the coordinates of the connection points to obtain a tunnel virtual scene. Specifically, the method comprises the following steps:
firstly, the highway tunnel can be segmented according to civil structure data, the tunnel is divided into a plurality of section tunnels, the civil structure data comprise the lining type of the tunnel, and the highway tunnel can be segmented according to the lining type. For example, the tunnel may be divided into a main tunnel, a pedestrian crosswalk tunnel, a vehicular crosswalk tunnel, and the like. The respective civil structure data of the individual segmental tunnels and the positions of the junctions between each other can be determined by the civil structure data of the road tunnel.
And then, constructing a jointed three-dimensional model of each section of tunnel according to the corresponding civil structure data. When the linking three-dimensional model of each section tunnel is constructed, as part of the section tunnels can present a lining type and the constructed linking three-dimensional model can be reused, the constructed linking three-dimensional model can be stored in a tunnel model component library, and when the linking three-dimensional model is used, the linking three-dimensional model corresponding to each section tunnel can be directly called from the tunnel model component library according to the requirements of a tunnel virtual scene. Therefore, the modeling workload can be effectively reduced, and the model construction efficiency is accelerated.
And finally, the three-dimensional models can be connected through the coordinates of the connection points among all the section tunnels, so that the complete tunnel three-dimensional model of the road tunnel is constructed, and the compatibility of the operation scene is not worried.
In this embodiment, preferably, as shown in fig. 3, constructing the connected three-dimensional model includes:
step 1-2-1, respectively creating three-dimensional coordinate systems perpendicular to the route at the end-to-end connection positions of the section tunnels;
step 1-2-2, constructing a structural outline of the sectional tunnel according to civil engineering structure data based on a three-dimensional coordinate system, and determining the coordinates of a joint point of the sectional tunnel;
step 1-2-3, constructing a three-dimensional model of a sectional tunnel according to a corresponding structural contour and a corresponding route;
step 1-2-4, establishing a solid three-dimensional model of the sectional tunnel based on the corresponding three-dimensional model;
step 1-2-5, performing Boolean difference set operation on the solid three-dimensional model of each section tunnel according to the connection point coordinates to obtain a corresponding connection three-dimensional model, specifically:
firstly, a coordinate system can be established at the head-to-tail connection position of the section tunnels along the route, so that the coordinates between the section tunnels are related, the coordinates between different section tunnels do not need to be converted during connection, and the three-dimensional models of the section tunnels can be conveniently and quickly connected and combined together.
Then, based on a three-dimensional coordinate system, a structural outline can be constructed according to civil engineering structure data corresponding to the sectional tunnels, then, three-dimensional models of the sectional tunnels are constructed through the structural outline, and then, based on the three-dimensional models of the sectional tunnels, 3ds MAX software is adopted to construct solid three-dimensional models of the sectional tunnels, such as solid three-dimensional models of a main hole, a vehicle crosshole, a pedestrian crosshole, an emergency parking area and the like.
And finally, linking the solid three-dimensional models of the section tunnels according to coordinates of linking points among the main tunnel, the crosswalk tunnel, the emergency parking zone and the like, and performing Boolean difference set operation on the solid three-dimensional models of the main tunnel by using the solid three-dimensional models of the crosswalk tunnel, the crosswalk tunnel and the emergency parking zone to obtain a linked three-dimensional model comprising the linking points corresponding to the main tunnel. And performing Boolean difference set operation on the three-dimensional models of the crosswalk hole and the crosswalk hole by using the solid three-dimensional model of the main hole to obtain a connected three-dimensional model which corresponds to the crosswalk hole and comprises connecting points.
In this embodiment, it is preferable that the method further includes:
packaging the jointed three-dimensional model of the section tunnel into a jointed three-dimensional assembly;
selecting corresponding connection three-dimensional components of tunnels of all sections, and connecting according to connection point coordinates to form the tunnel virtual scene. The method is beneficial to model multiplexing and updating optimization, and a complete tunnel virtual scene is quickly assembled according to the physical scene of the highway tunnel.
In this embodiment, preferably, the processing the real-time data includes: and carrying out noise reduction, abnormal value elimination and missing data compensation on the real-time data.
When processing the real-time data, firstly, wavelet transformation can be carried out on the data containing noise by adopting a wavelet denoising method, the noise contained in the real-time data is removed through a wavelet coefficient obtained through transformation, and the denoised data is obtained by carrying out wavelet inverse transformation on the processed wavelet coefficient, so that the reliability of the data is improved. Then, abnormal data in the noise reduction processing process are removed, and the data are arranged according to time sequence to obtain data suitable for subsequent work. And finally, compensating the missing data, wherein the compensation mode can be divided into first and last data compensation and intermediate data compensation according to different positions of the data, the first and last data compensation is used for compensating the missing data at the beginning or the end according to the trend of the missing data, and the intermediate data compensation is realized by adopting a polynomial interpolation method so as to ensure the integrity of the data.
In this embodiment, preferably, as shown in fig. 4, the predicting the maintenance time of the physical device includes:
step 3-1-1, determining the current degradation state of the physical equipment according to the state data;
step 3-1-2, determining a state measurement value when the corresponding test equipment is in the degradation state and the fault time when the test equipment has faults;
3-1-3, calculating a similarity parameter between the physical equipment and the test equipment according to the state data and the state measured value;
3-1-4, predicting the maintenance time of the physical equipment according to the similarity parameter and the failure time;
and 3-1-5, correcting the maintenance time of the physical equipment through a confidence function theory. Specifically, the method comprises the following steps:
in this embodiment, a fuzzy similarity method may be used to predict the remaining service life of the physical device, that is, predict the maintenance time of the physical device, and apply the confidence function theory to the uncertainty processing. The confidence function theory can eliminate the uncertainty of predicting the service life by using the fuzzy similarity theory as far as possible under the condition of little state data, and the method comprises the following specific steps:
first, each degradation state corresponds to corresponding state data, so that the degradation state of the physical device can be determined according to the current state data of the physical device.
The state measurements of the test device in said degraded state and the time to failure of the test device after said degraded state can then be determined from historical test data of the test device. The remaining service life RUL of the test equipment can be calculated through the failure time and the current timer：
Wherein,
for the time that the test device fails after being in said degraded state,
is the current time.
Then, a similarity parameter between the current degradation state of the physical device and the test device can be calculated according to the state estimation value of the physical device and the state measurement value of the test device, and the similarity parameter is calculated as follows:
where λ is a value that minimizes the error of the similarity-based prediction calculated on the validation dataset, and takes a value of 5 × 10-5The accuracy of the prediction can be improved to the maximum extent,
is a state measurement of the test equipment in a degraded state,
is a state estimate value for a physical device in the same degraded state,
is the variance of the state values when the test equipment and the physical equipment are in the same degradation state.
Then, the remaining service life of the physical device, i.e. the maintenance time RUL of the physical device, can be predicted by testing the remaining service life of the device and the similarity parameter:
wherein,
is the similarity parameter of the current time calculated by using the above similarity parameters.
And finally, correcting the predicted maintenance time according to a confidence function theory, and eliminating the uncertainty of predicting the maintenance time by using a fuzzy similarity theory. Therefore, even if the quantity of the state data of the physical equipment or the state measurement values of the test equipment is small, the uncertainty of the fuzzy similarity method on the prediction result can be eliminated, and the accuracy of the maintenance time is improved, wherein the specific calculation method comprises the following steps:
wherein gamma is the confidence of the equipment degradation track set and takes the value of [0, 1%]，mRULIs the corrected maintenance time.
In this embodiment, preferably, creating the digital twin model includes:
constructing digital twin models in different forms according to scene characteristic quantity data of physical equipment;
and defining a data interface between the digital twin models with different forms and scene characteristic quantity data of the physical equipment. The data interface is used for switching the digital twin model morphology when the scene characteristic quantity data of the physical equipment exceeds a preset range.
And acquiring real-time scene characteristic quantity data of the physical equipment, and matching the digital twin model with a corresponding form through a data interface to assemble the digital twin model into a tunnel virtual scene.
Specifically, the real-time scene feature quantity data may be compared with scene feature quantity data corresponding to digital twin models of different forms, and if the real-time scene feature quantity data is within a feature quantity data range of a digital twin model of a certain form, the digital twin model matched with the form is injected into the tunnel virtual scene; and if the real-time scene characteristic quantity data exceeds the scene characteristic quantity data range of the digital twin model in the current form, matching the digital twin model in the corresponding scene characteristic quantity data range and assembling the digital twin model into the tunnel virtual scene, thereby intuitively and really reflecting the running state in the tunnel in real time.
In this embodiment, it is preferable that the method further includes:
defining a data interface between digital twin models of different forms and state data of physical equipment; the data interface between the digital twin model and the state data of the physical device can be used for switching the digital twin model form when the state of the object device changes, so that the running state in the tunnel is truly reflected.
And acquiring real-time state data of the physical equipment, and assembling the real-time state data into a tunnel virtual scene by matching the digital twin model with a corresponding form through a data interface.
Specifically, the real-time state data may be compared with state data corresponding to digital twin models of different forms, and if the real-time state data is within the state data range of a digital twin model of a certain form, the digital twin model matched with the form is injected into the tunnel virtual scene; and if the real-time state data exceeds the state data range of the digital twin model in the current state, matching the digital twin model in the corresponding state data range and assembling the digital twin model into the tunnel virtual scene, so that the running state in the tunnel is intuitively and really reflected in real time.
A storage medium stores a computer program which, when running, executes the above-described simulation method.
The above examples are only intended to illustrate the technical solution of the present invention, but not to limit it; while the invention has been described in detail and with reference to the foregoing embodiments, it will be understood by those skilled in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some or all of the technical features may be equivalently replaced; such modifications and substitutions do not depart from the spirit and scope of the present invention, and they should be construed as being included in the following claims and description.
Claims (9)
1. A road tunnel running state simulation method based on a digital twin model is characterized by comprising the following steps:
constructing a tunnel virtual scene of the highway tunnel according to the corresponding civil structure data;
acquiring real-time data of physical equipment in a highway tunnel to perform data processing to obtain state data reflecting the state of the physical equipment and scene characteristic quantity data reflecting the running state of the tunnel;
predicting the maintenance time of corresponding physical equipment through state data, and creating a corresponding digital twin model in the tunnel virtual scene according to scene characteristic quantity data, wherein the digital twin model carries out model evolution along with the change of the scene characteristic quantity data;
and judging whether the maintenance time of the physical equipment is reached, and in response to the reaching of the maintenance time, creating a corresponding digital twin model in the tunnel virtual scene according to the scene characteristic quantity data again.
2. The method for simulating the running state of the road tunnel based on the digital twin model as claimed in claim 1, wherein constructing the tunnel virtual scene comprises:
dividing the tunnel into a plurality of section tunnels according to the civil structure data of the highway tunnel, and determining the civil structure data and the connection points of each section tunnel;
constructing a connection three-dimensional model of each section of tunnel through corresponding civil engineering structure data, and determining connection point coordinates among the sections of tunnels;
and connecting the three-dimensional model of each section of tunnel according to the coordinates of the connecting points to obtain a tunnel virtual scene.
3. The method for simulating the running state of the road tunnel based on the digital twin model as claimed in claim 2, wherein constructing the jointed three-dimensional model comprises:
respectively creating three-dimensional coordinate systems perpendicular to the route at the head-tail connection positions of the section tunnels;
based on a three-dimensional coordinate system, constructing a structural outline of the sectional tunnel according to civil engineering structure data, and determining the coordinates of the joint points of the sectional tunnel;
constructing a three-dimensional model of the sectional tunnel according to the corresponding structural outline and the route;
creating a solid three-dimensional model of the segmental tunnel based on the corresponding three-dimensional model;
and carrying out Boolean difference set operation on the solid three-dimensional model of each section tunnel according to the coordinates of the joint points to obtain a corresponding joint three-dimensional model.
4. The method for simulating the running state of the road tunnel based on the digital twin model as claimed in claim 2, further comprising:
packaging the jointed three-dimensional model of the section tunnel into a jointed three-dimensional assembly;
selecting corresponding connection three-dimensional components of tunnels of all sections, and connecting according to connection point coordinates to form the tunnel virtual scene.
5. The method for simulating the running state of the road tunnel based on the digital twin model as claimed in claim 1, wherein the processing of the real-time data comprises: and carrying out noise reduction, abnormal value elimination and missing data compensation on the real-time data.
6. The method for simulating the running state of the road tunnel based on the digital twin model according to claim 1, wherein predicting the maintenance time of the physical equipment comprises:
determining the current degradation state of the physical equipment according to the state data;
determining a state measurement value when the corresponding test equipment is in the degradation state and fault time when the test equipment fails;
calculating a similarity parameter between the physical equipment and the test equipment according to the state data and the state measured value;
predicting the maintenance time of the physical equipment according to the similarity parameter and the failure time;
and correcting the maintenance time of the physical equipment through a confidence function theory.
7. The method for simulating the running state of the road tunnel based on the digital twin model according to claim 1, wherein the creating of the digital twin model comprises:
constructing digital twin models in different forms according to scene characteristic quantity data of physical equipment;
defining a data interface between digital twin models with different forms and scene characteristic quantity data of physical equipment;
and acquiring real-time scene characteristic quantity data of the physical equipment, and matching the digital twin model with a corresponding form through a data interface to assemble the digital twin model into a tunnel virtual scene.
8. The method for simulating the running state of the road tunnel based on the digital twin model as claimed in claim 7, further comprising:
defining a data interface between digital twin models of different forms and state data of physical equipment;
and acquiring real-time state data of the physical equipment, and assembling the real-time state data into a tunnel virtual scene by matching the digital twin model with a corresponding form through a data interface.
9. A storage medium storing a computer program, wherein the computer program is executed to perform the method for simulating the operation state of a road tunnel based on a digital twin model according to any one of claims 1 to 8.
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| CN114548512A (en) * | 2022-01-19 | 2022-05-27 | 福建工程学院 | Road operation data estimation method and device for digital twins |
| CN114936409A (en) * | 2022-06-24 | 2022-08-23 | 福州大学 | Digital twinning modeling method for civil engineering structure |
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| CN114936409A (en) * | 2022-06-24 | 2022-08-23 | 福州大学 | Digital twinning modeling method for civil engineering structure |
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