CN111862323A - Multi-element pregnant disaster digital twin intelligent perception identification early warning system and method - Google Patents
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Abstract
The invention provides a multivariate pregnancy disaster digital twin intelligent perception identification early warning system and a method thereof, which relate to the technical field of mine production, can realize effective complementation of virtual and reality, have more accurate information utilization and are beneficial to dynamically adjusting an exploitation scheme; the method comprises the following steps: s1, modeling according to the real mining environment to obtain a stratum model; s2, carrying out lightweight processing and modeling on the mining equipment, the supporting equipment and the monitoring equipment to obtain an equipment model; s3, importing the equipment model into the stratum model to obtain a final digital twin model; s4, demonstrating the mining process in the digital twin model in advance, judging whether the mining process is safe according to the demonstration result, and mapping the mining process to the actual mining process; and S5, feeding back the result of real mining to the digital twin model, realizing real and virtual repeated verification and comparison, and adjusting the model according to the result of verification and comparison. The technical scheme provided by the invention is suitable for the process of mining.
Description
[ technical field ] A method for producing a semiconductor device
The invention relates to the technical field of mine production, in particular to a multivariate pregnancy disaster digital twin intelligent perception identification early warning system and a multivariate pregnancy disaster digital twin intelligent perception identification early warning method.
[ background of the invention ]
With the development of economy in China, the demand for coal mine resources is improved, and the number of mines is greatly increased. Rock burst is one of the most serious dynamic disasters in coal mines, and causes huge damage and loss. With the increase of mining depth, the increase of mining range and the improvement of mining intensity, the occurrence frequency of rock burst of mines all over the country is gradually increased and gradually worsened. However, in the face of rock burst, the problems that a multi-parameter combined early warning and monitoring system is not established yet, the control operation and maintenance digitization level is low and the like still restrict mining. The digital twin technology is combined with mine production construction, mining roadway model simulation based on the digital twin is developed, a user can better master coal seam mining conditions, and the rock burst problem can be quickly and accurately processed.
The digital twin is a simulation process integrating multidisciplinary, multi-physical quantity, multi-scale and multi-probability by fully utilizing data such as a physical model, sensor updating, operation history and the like, and mapping is completed in a virtual space, so that the full life cycle process of corresponding entity equipment is reflected. A virtual tunnel is established through a three-dimensional modeling method, and bidirectional real mapping and real-time interaction of a real tunnel and the virtual tunnel are realized by utilizing a digital twin technology, so that real-time monitoring of the mining process and equipment and early warning of dynamic disasters of the tunnel are realized. Data acquisition refers to the process of automatically acquiring information from analog and digital units under test, such as sensors and other devices under test. If the digital twinning technology and the data acquisition technology can be combined to associate the roadway with the mining process, the early warning effect on the mining process can be well played.
Therefore, there is a need to develop a multiple pregnancy disaster digital twin intelligent perception recognition early warning system and method to overcome the deficiencies of the prior art, so as to solve or alleviate one or more of the above problems.
[ summary of the invention ]
In view of the above, the invention provides a multivariate pregnancy disaster digital twin intelligent perception identification early warning system and method, which can realize effective complementation of virtual and reality, make information utilization more accurate, and facilitate dynamic adjustment of an exploitation scheme.
In one aspect, the invention provides a multivariate pregnancy disaster digital twin intelligent perception identification early warning method, which is characterized by comprising the following steps:
s1, performing three-dimensional modeling according to the real mining environment and by combining a plane design drawing to obtain a stratum model;
s2, carrying out lightweight treatment on the mining equipment, the supporting equipment and the monitoring equipment, and then carrying out modeling to obtain an equipment model;
s3, importing the equipment model into the stratum model to obtain a final digital twin model;
s4, demonstrating the mining process in the digital twin model in advance, judging whether the mining process is safe according to the demonstration result, and mapping the mining process to the actual mining process;
and S5, feeding back the result of real mining to the digital twin model, realizing real and virtual repeated verification and comparison, and adjusting the model according to the result of verification and comparison.
The above-described aspects and any possible implementation further provide an implementation that enables the simulated environment of the digital twin model to be consistent with the real environment by a combination of:
the first method is as follows: updating the digital twin model according to real environment data acquired in real time;
the second method comprises the following steps: and comparing the simulation result with an actual manual field measurement result at regular intervals, and adjusting the digital twin model according to the comparison result.
As for the above-mentioned aspect and any possible implementation manner, there is further provided an implementation manner, and the specific content of step S4 includes: and inputting a next mining scheme into the model and simulating to realize the advance demonstration of the mining process in the model, judging whether the mining process is safe or not according to the demonstration result, if so, continuing the actual mining, and otherwise, adjusting the mining scheme according to the demonstration result to ensure the safety of the mining process.
As to the above-described aspects and any possible implementation, there is further provided an implementation in which adjusting the mining scheme specifically includes: reduce the production rate, increase the support pressure and/or adopt a pressure relief production scheme.
The above-described aspects and any possible implementation manner further provide an implementation manner, and the criteria for determining that the demonstration result is safe are as follows: the support resistance is less than 1.2 times of the support working resistance.
The above aspects and any possible implementation further provide an implementation manner, and when the support resistance is larger than or equal to 1.2 times of the support working resistance, an alarm is given.
The above aspects and any possible implementation manners further provide an implementation manner that actual operation data of the mining equipment, the supporting equipment and the monitoring equipment are collected in real time and input into the equipment model, and the performance state, the energy consumption peak value and the wear condition of the equipment are predicted by the equipment model, and a predictive maintenance scheme is given.
In the above aspect and any possible implementation manner, there is further provided an implementation manner that the data monitored by the monitoring device includes a rock energy value, and when the rock energy value is greater than or equal to 108And J, early warning is started, the recovery rate is reduced, and rock mass drilling pressure relief is carried out, so that energy release is realized.
In another aspect, the present invention provides a multivariate pregnancy disaster digital twin intelligent perception identification early warning system, which is characterized in that the system is used for implementing any one of the above early warning methods; the system comprises a digital twin model combining a stratum model and an equipment model, and is used for simulating and simulating the mining process, realizing monitoring, demonstrating the mining process in advance, judging whether the mining process is safe or not according to the demonstration result, and mapping the mining process to the actual mining process.
In a further aspect, the present invention provides a storage medium storing a program, characterized in that the program, when executed, causes an apparatus to carry out the steps as described in any of the above.
Compared with the prior art, the invention can obtain the following technical effects: the method of mutual adjustment between the virtual mode and the real mode is adopted, information sharing is achieved, the virtual mode and the real mode are complementary, information utilization is more accurate, dynamic adjustment of the mining scheme is facilitated, and optimal mining is achieved.
Of course, it is not necessary for any one product in which the invention is practiced to achieve all of the above-described technical effects simultaneously.
[ description of the drawings ]
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings needed to be used in the embodiments will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art to obtain other drawings based on these drawings without creative efforts.
FIG. 1 is a flow chart of a digital twin based mining roadway simulation method provided by one embodiment of the present invention;
FIG. 2 is a digital twin model diagram of a mining roadway provided in accordance with an embodiment of the present invention;
Fig. 3 is a schematic diagram of a digital twin-based mining roadway simulation method according to an embodiment of the present invention.
[ detailed description ] embodiments
For better understanding of the technical solutions of the present invention, the following detailed descriptions of the embodiments of the present invention are provided with reference to the accompanying drawings.
It should be understood that the described embodiments are only some embodiments of the invention, and not all embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
The terminology used in the embodiments of the invention is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention. As used in the examples of the present invention and the appended claims, the singular forms "a," "an," and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise.
A mining roadway simulation method based on digital twinning is disclosed, as shown in figure 1, and comprises the following steps:
step 1, establishing a twin virtual model similar to mining engineering, namely a stratum model: on the basis of simulation software, according to a real mining environment and in combination with a plane design drawing, carrying out three-dimensional modeling on mining to obtain a mining twin virtual model, wherein the twin virtual model comprises a mechanical model, a physical model, a geometric model and an information model;
A mining model is established on 3D software such as 3D Max, data in mining are presented in a three-dimensional mode, a user utilizes the 3D Max software to operate the model of a roadway key area so as to display all information including geological conditions in the area and geological change conditions moving along with time, and potential dangers such as the actual position and the size of equipment at the position, cracks on the terrain, strain of mining surrounding rocks and the like are found by rotating and zooming an image at the position.
Step 2, carrying out lightweight treatment on the mining roadway equipment, the supporting device, the sensor and the like, and modeling and importing the physical entity of the mining roadway equipment, the supporting device, the sensor and the like to a model simulation platform;
2.1 establishing digital twin models (namely equipment models) of mining equipment, supporting equipment, sensors and the like in Flexsim, ProModel, Witness or Visual Components virtual simulation software, and introducing the digital twin models into the mining engineering twin virtual models established in the step 1), namely, placing specific mining equipment and monitoring equipment into a stratum model, so that the two models are combined to embody a real mining environment.
Meanwhile, updating environmental data in real time to make the model environment consistent with the mining real environment, comprising: temperature, mechanical state, displacement, vibrations, mining speed to leading-in earlier stage reconnaissance and experimental data simultaneously, including data such as coal rock mass compressive strength, tunnel radius, coal seam thickness define through Python, the built-in function of C # script editor drive virtual simulation software, realize that data, state change and the parameter in tunnel are visual. In order to make the simulation environment consistent with the real environment, various data which are really collected are input, the simulation result is regularly compared with the actual manual field test result, and the model is dynamically adjusted in time according to the comparison result.
Mirroring: the digital twin provides a virtual real model and a transparent construction of scenes, like a mirror principle, an actual mining process can be transparently displayed in the virtual transparent model, meanwhile, the virtual transparent model can work ahead, advance work is previewed in the transparent model, a previewing result can also be obtained, if the virtual transparent model is safe, actual mining can follow, if unsafe signs appear, the virtual transparent model is mapped to actual mining, the mining speed is changed, or supporting pressure or pressure relief mining and the like are changed. Meanwhile, the scheme and the result of actual mining are fed back to the virtual transparent model, the virtual result and the real result can be compared in time, the comparison is verified repeatedly, and the virtual transparent model can provide a more reasonable, accurate and safe mining scheme for actual mining. The advanced work is to input the next mining scheme in the virtual transparent model in advance, for example, the mining speed is 5m/d, so that the states of deformation, support pressure and the like under the mining condition can be displayed in advance, and the condition after the next mining can be known in advance. The judgment standard of whether the safety is ensured is as follows: and uniformly judging by adopting a support resistance index, judging that the support resistance is unsafe when the support resistance is more than 1.2 times greater than the working resistance of the support, giving an alarm, and judging that the support resistance is safe when the support resistance is less than 1.2 times. The virtual transparent model is a mining twin virtual model obtained by three-dimensional modeling of mining according to a real mining environment and combining a plane design drawing. Virtual reality model and scene transparent construction refer to a concept that a digital twin provides a virtual model similar to reality, and this model is transparent and visible. The combined model of the equipment model and the stratum model represents a real-like three-dimensional mining virtual model, and the transparent visualization means that entities such as equipment, a stratum, a coal bed and the like can be transparently displayed.
The mapping relation is as follows: in the virtual transparent model and the actual mining process, because the increase of the support resistance and the support deformation are synchronous, the support resistance index is adopted for early warning. And (4) when the support resistance is 1.2 times larger than the working resistance of the bracket, giving an alarm (namely the safety judgment standard). After the alarm is given, the mining speed or the supporting pressure or the pressure relief mining scheme and the like need to be adjusted.
Mutual adjustment of virtual and real: the virtual transparent model can work in advance, the advance work is previewed into the transparent model in advance, a previewing result can be obtained, if the virtual transparent model is safe, actual mining can follow, if unsafe signs appear, the virtual transparent model is mapped to actual mining, the mining speed or supporting pressure or pressure relief mining is changed, and the like until an optimal reasonable mining scheme is adjusted.
The method of mutual adjustment between the virtual information and the reality is beneficial to information sharing, namely virtual information and reality information sharing, so that the complementation between the virtual information and the reality is achieved, the information utilization is more accurate, and the dynamic adjustment of the mining scheme is facilitated. Such as: the support resistance is too high under the condition that the virtual advance preview extraction rate is achieved, the extraction rate is reduced in reality, the support resistance under the real condition is extracted, and if the support resistance does not reach the early warning, the support resistance is fed back to the virtual model to achieve the real extraction rate, so that the purpose of dynamic adjustment can be achieved. The method is beneficial to data accumulation and big data analysis, and like the contents, all data and adjustment schemes are recorded in the model, so that the risk schemes can be reasonably selected and avoided according to the adopted schemes, the virtual model can also carry out memory processing on a large number of recovery schemes, and risk analysis is carried out on the input schemes, so that a user can reasonably adopt the recovery schemes. Therefore, the purposes of virtual and real complementation, scheme dynamic adjustment and reasonable optimization adjustment can be achieved.
The stratum model is mainly used for establishing three-dimensional geological structure morphology, giving strength parameters to each stratum, boundary conditions of each stratum and mining conditions. The equipment model mainly comprises the steps of constructing equipment appearance, structure, arrangement position, working parameters and the like. And importing the equipment model into the bottom model to realize the combination of the equipment model and the bottom model.
According to the digital twin method for mining engineering, preferably, a mining model based on digital twin simulates different mining processes, effects under different scenes are compared, feasibility and stability of the mining process are verified, mining efficiency of the mining process is evaluated, immature and unstable mining processes are avoided, so that a mining scheme is optimized, and engineering implementation is guided. The digital twinning is a technical means or an informatization concept, displays a dynamic process by manufacturing a real scene, tries to realize real visualization, and comprises the steps of constructing a stratum model approaching to the real stratum (constructed according to acquired original stratum data) and acquiring real dynamic data for updating, wherein the two data are obtained by acquiring the dynamic data at the later stage and endowing the dynamic data to specific parameters in the original stratum model so as to realize more real coupling and interaction change.
According to the mining engineering digital twinning method, preferably, operation data of mining equipment, supporting equipment and monitoring equipment are collected in real time, performance states, energy consumption peak values and abrasion conditions of the equipment are predicted, predictive maintenance is given, when parameters of the equipment are abnormal, prompt is immediately carried out in a system, fault phenomena are rapidly analyzed, fault positions are located, the fault positions are pushed to relevant users through relevant service application systems, and corresponding measures are taken to reduce construction risks. And pre-judging the data development trend according to the dynamic change rule of the monitoring data, and judging the current working state according to the working threshold values of different equipment, wherein each type of equipment has a corresponding maintenance scheme.
The monitoring data mainly comprises: the deformation value, the support pressure and the rock mass energy value are continuously changed along with the advancing of a stope working face and the increasing of the distance from the working face, for example, the deformation value and the support pressure are gradually stable after being continuously increased along with the advancing of the working face, and if the initial pressure or the periodic pressure is met, the support pressure is increased in a jumping manner; the energy of the rock mass can be continuously increased along with the propulsion of the working face, and can be reduced after unloading. And (3) early warning when the support pressure is 1.2 times greater than the support working resistance according to the change rule of the deformation value and the support pressure, and reducing the extraction rate, increasing the support working resistance or adopting a pressure relief extraction scheme according to a corresponding adjustment scheme. The prejudging standard of rock mass energy trend is to firstly determine an energy accumulation space region, and when the maximum energy accumulation value of the rock mass reaches 108And J, early warning is started, and the corresponding adjustment scheme is to reduce the recovery rate and relieve the pressure of the rock body drilling hole, so that the accumulated energy cracks are released for pressure relief.
According to the mining engineering digital twinning method, preferably, virtual simulation software is developed secondarily and is interacted with engineering analysis software such as MATLAB, ADAMS, ANSYS, FLAC 3D and the like in real time to obtain action data and states. For example, the real-time stress state of the roadway returns to the monitoring system through data such as surrounding rock deformation, drilling stress, micro-shock, support load and the like, enters ANSYS through the interface to perform stress analysis on the roadway, and returns the real-time operation analysis result to the virtual model for real-time presentation. Namely: important results such as the distribution condition of the main stress, the deformation state, the energy transfer and the like are returned to supplement and perfect the result of the virtual model; the main content of the analysis and the content of the return are the same for different mining projects, since the main factors of the mining project are stress distribution, deformation state, energy transfer. The content of the secondary development comprises the development of an embedded interface program, namely, the three-dimensional stratum model and the acquired data information thereof are imported into numerical calculation software for stress and result analysis.
Step 3, collecting real-time data of all dimensions such as mining coal seam geological conditions, environmental parameters, roadway tunneling parameters and equipment running states, and storing the real-time data into a database to be uploaded to a cloud;
3.1, establishing communication between the roadway and the simulation model: the sensor device in the tunnel is connected with a database system through different interfaces, and then data collected by the database system is sent to a tunnel virtual model in virtual simulation software (such as 3DMax) based on a Socket UDP protocol; the data of the tunnel virtual model is a data receiving interface established through Socket UDP, a data feedback interface established through Modbus TCP/IP, and a compiled data processing script is used for driving data feedback and various monitoring data display of the twin virtual model of the tunnel in real time.
3.2, according to the mining engineering digital twin method, preferably, the database in the step (3) can be a MySQL database.
And 4, calling real-time data in the database by the model simulation platform, driving the evolution development of the roadway model according to the real-time data, and finally serving and applying the roadway model.
The above describes in detail a multivariate pregnancy digital twin intelligent perception identification early warning system and method provided by the embodiments of the present application. The above description of the embodiments is only for the purpose of helping to understand the method of the present application and its core ideas; meanwhile, for a person skilled in the art, according to the idea of the present application, there may be variations in the specific embodiments and the application scope, and in summary, the content of the present specification should not be construed as a limitation to the present application.
As used in the specification and claims, certain terms are used to refer to particular components. As one skilled in the art will appreciate, manufacturers may refer to a component by different names. This specification and claims do not intend to distinguish between components that differ in name but not function. In the following description and in the claims, the terms "include" and "comprise" are used in an open-ended fashion, and thus should be interpreted to mean "include, but not limited to. "substantially" means within an acceptable error range, and a person skilled in the art can solve the technical problem within a certain error range to substantially achieve the technical effect. The description which follows is a preferred embodiment of the present application, but is made for the purpose of illustrating the general principles of the application and not for the purpose of limiting the scope of the application. The protection scope of the present application shall be subject to the definitions of the appended claims.
It is also noted that the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a good or system that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such good or system. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other like elements in a commodity or system that includes the element.
It should be understood that the term "and/or" as used herein is merely one type of association that describes an associated object, meaning that three relationships may exist, e.g., a and/or B may mean: a exists alone, A and B exist simultaneously, and B exists alone. In addition, the character "/" herein generally indicates that the former and latter related objects are in an "or" relationship.
The foregoing description shows and describes several preferred embodiments of the present application, but as aforementioned, it is to be understood that the application is not limited to the forms disclosed herein, but is not to be construed as excluding other embodiments and is capable of use in various other combinations, modifications, and environments and is capable of changes within the scope of the application as described herein, commensurate with the above teachings, or the skill or knowledge of the relevant art. And that modifications and variations may be effected by those skilled in the art without departing from the spirit and scope of the application, which is to be protected by the claims appended hereto.
Claims (10)
1. A multivariate pregnancy disaster digital twin intelligent perception identification early warning method is characterized by comprising the following steps:
s1, performing three-dimensional modeling according to the real mining environment and by combining a plane design drawing to obtain a stratum model;
S2, carrying out lightweight treatment on the mining equipment, the supporting equipment and the monitoring equipment, and then carrying out modeling to obtain an equipment model;
s3, importing the equipment model into the stratum model to obtain a final digital twin model;
s4, demonstrating the mining process in the digital twin model in advance, judging whether the mining process is safe according to the demonstration result, and mapping the mining process to the actual mining process;
and S5, feeding back the result of real mining to the digital twin model, realizing real and virtual repeated verification and comparison, and adjusting the model according to the result of verification and comparison.
2. The multi-pregnancy disaster digital twin intelligent perception recognition early warning method as claimed in claim 1, wherein the simulated environment of the digital twin model is consistent with the real environment by the combination of the following two ways:
the first method is as follows: updating the digital twin model according to real environment data acquired in real time;
the second method comprises the following steps: and comparing the simulation result with an actual manual field measurement result at regular intervals, and adjusting the digital twin model according to the comparison result.
3. The method for intelligent perception, identification and early warning of multiple pregnancy disasters according to claim 1, wherein the step S4 comprises the following steps: and inputting a next mining scheme into the model and simulating to realize the advance demonstration of the mining process in the model, judging whether the mining process is safe or not according to the demonstration result, if so, continuing the actual mining, and otherwise, adjusting the mining scheme according to the demonstration result to ensure the safety of the mining process.
4. The multi-pregnancy disaster digital twin intelligent perception, identification and early warning method according to claim 3, wherein adjusting the mining scheme specifically comprises: reduce the production rate, increase the support pressure and/or adopt a pressure relief production scheme.
5. The multi-element pregnancy disaster digital twin intelligent perception, identification and early warning method as claimed in claim 3, wherein the demonstration result is judged as safe standard: the support resistance is less than 1.2 times of the support working resistance.
6. The multi-element pregnancy disaster digital twin intelligent sensing, identifying and early warning method according to claim 5, characterized in that when the support resistance is more than or equal to 1.2 times the working resistance of the support, an alarm is given.
7. The multi-element pregnancy disaster digital twin intelligent perception recognition early warning method as claimed in claim 1, wherein the actual operation data of the mining equipment, the supporting equipment and the monitoring equipment are collected in real time and input into the equipment model, the performance state, the energy consumption peak value and the abrasion condition of the equipment are predicted by the equipment model, and a predictive maintenance scheme is given.
8. The multi-element pregnancy disaster digital twin intelligent sensing, identifying and early warning method as claimed in claim 1, wherein the data monitored by the monitoring device includes rock energy value, when the rock energy value is greater than or equal to 10 8And J, early warning is started, the recovery rate is reduced, and rock mass drilling pressure relief is carried out, so that energy release is realized.
9. A multivariate pregnancy disaster digital twin intelligent perception recognition early warning system, which is used for realizing the early warning method according to any one of claims 1-8; the system comprises a digital twin model combining a stratum model and an equipment model, and is used for simulating and simulating the mining process, realizing monitoring, demonstrating the mining process in advance, judging whether the mining process is safe or not according to the demonstration result, and mapping the mining process to the actual mining process.
10. A storage medium storing a program, wherein the program, when executed, causes an apparatus to carry out the steps of any of claims 1-8.
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| CN112329183A (en) * | 2020-11-06 | 2021-02-05 | 北京三一智造科技有限公司 | Equipment state data acquisition method and device, electronic equipment and storage medium |
| CN112394667A (en) * | 2020-11-24 | 2021-02-23 | 长江勘测规划设计研究有限责任公司 | Construction process safety monitoring method based on digital twinning |
| CN113221461A (en) * | 2021-05-20 | 2021-08-06 | 太原理工大学 | Tunneling and anchoring all-in-one machine monitoring system based on digital twin technology |
| CN113487138A (en) * | 2021-06-09 | 2021-10-08 | 中国民航大学 | Airport emergency drilling method and system based on digital twins |
| CN113504737A (en) * | 2021-05-11 | 2021-10-15 | 中钢集团马鞍山矿山研究总院股份有限公司 | Multi-element pregnant disaster digital twin intelligent perception identification early warning system and method |
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| CN115221704A (en) * | 2022-07-18 | 2022-10-21 | 应急管理部国家自然灾害防治研究院 | Geological disaster deduction method and system based on digital twin simulation platform |
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| CN112329183A (en) * | 2020-11-06 | 2021-02-05 | 北京三一智造科技有限公司 | Equipment state data acquisition method and device, electronic equipment and storage medium |
| CN112394667A (en) * | 2020-11-24 | 2021-02-23 | 长江勘测规划设计研究有限责任公司 | Construction process safety monitoring method based on digital twinning |
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| CN113515848A (en) * | 2021-05-13 | 2021-10-19 | 三一重型装备有限公司 | Method and system for optimizing structural design of mining equipment and readable storage medium |
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| CN113792422A (en) * | 2021-09-04 | 2021-12-14 | 苏州特比姆智能科技有限公司 | TPM (trusted platform Module) equipment management virtual verification method and system based on digital twin |
| CN113792422B (en) * | 2021-09-04 | 2023-12-05 | 苏州特比姆智能科技有限公司 | Digital twinning-based TPM equipment management virtual verification method and system |
| WO2023185735A1 (en) * | 2022-03-28 | 2023-10-05 | 中国矿业大学 | Mine stress field twin modeling assimilation system for full space-time mining process, and method |
| CN115221704A (en) * | 2022-07-18 | 2022-10-21 | 应急管理部国家自然灾害防治研究院 | Geological disaster deduction method and system based on digital twin simulation platform |
| CN115238553A (en) * | 2022-07-27 | 2022-10-25 | 北京科技大学 | Method and system for dividing dangerous area of buried pipeline leakage erosion |
| CN115238553B (en) * | 2022-07-27 | 2023-03-10 | 北京科技大学 | Method and system for dividing dangerous area of buried pipeline leakage erosion |
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