Pipe network system, pipe data processing method and processor based on multi-modal fusion

Abstract

The embodiment of the application provides a kind of based on multi-modal fusion pipe network system, pipe data method and processor of effortful.The method comprises: edge service platform is used to obtain the real-time state and behavior information of entity pipe, and the real-time state and behavior information are introduced into the all-element data model resource pool;All-element data model resource pool is used to store the element data and model of entity pipe, and according to the real-time state and behavior information introduced by edge service platform, the stored element data and model are updated and optimized;Multi-domain modeling analysis center, including multi-modal fusion analysis engine, multi-domain modeling analysis center is used to determine target entity pipe according to demand, and the real-time element data and model of target entity pipe obtained by all-element data model resource pool are introduced into multi-modal fusion analysis engine.Drive kernel is provided by multi-domain modeling analysis center, and all-element data model resource pool provides data stream and model, and edge service platform realizes light weight operation.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of pipeline operation management, and in particular to a pipeline network system based on multi-modal fusion, a pipeline data processing method and device, a processor, a storage medium and a computer program product. BACKGROUND

[0002] With the construction of various production business management systems such as pipeline design systems, SCADA systems, GIS systems, integrity management systems and the continuous development of information technology, the pipeline digital management mode has achieved remarkable improvement effect in operation regulation and control, integrity management and the like. However, with the continuous deepening of the exploration and practice of pipeline intelligentization in China in recent years, the pipeline construction and operation management is facing the barrier of multiple business systems, forming a large number of information islands, and the massive data assets cannot be efficiently utilized and deeply mined. The energy level of the model-driven technology in the pipeline operation management is insufficient, and other pain points seriously restrict the further intelligent transformation and upgrading of the pipeline industry. SUMMARY

[0003] The purpose of the embodiments of the present application is to provide a pipeline network system based on multi-modal fusion, a pipeline data processing method and device, a processor, a storage medium and a computer program product.

[0004] In order to achieve the above-mentioned purpose, the first aspect of the present application provides a pipeline network system based on multi-modal fusion, which comprises a pipeline digital twin platform, comprising:

[0005] An edge service platform is configured to acquire real-time state and behavior information of an entity pipeline and import the real-time state and behavior information into a full-factor data model resource pool;

[0006] The full-factor data model resource pool is configured to store factor data and models of the entity pipeline and update and optimize the stored factor data and models according to the real-time state and behavior information imported by the edge service platform;

[0007] A multi-domain modeling and analysis center comprises a multi-modal fusion analysis engine, and is configured to determine a target entity pipeline according to a demand, import real-time factor data and models of the target entity pipeline acquired through the full-factor data model resource pool into the multi-modal fusion analysis engine, model and analyze and evaluate the real-time factor data and models of the target entity pipeline through the multi-modal fusion analysis engine, and determine a final solution for the target entity pipeline.

[0008] Optionally, the factor data comprises at least one of pipe body data, environmental data, fluid medium, equipment attribute, real-time operation data and historical operation data of the entity pipeline.

[0009] Optionally, the multi-modal fusion analysis engine comprises a data analysis engine and a multi-physical field simulation engine, the data analysis engine comprises a plurality of analysis functions and a tool corresponding to each analysis function, wherein the analysis functions comprise at least one of a data mining function, a data statistical function and a machine learning function, and the multi-physical field simulation engine comprises at least one of a modeling engine function, a map engine function and a model management function.

[0010] Optionally, the pipe network system further comprises: a pipe entity perception system connected with the entity pipe, configured to perceive an abnormal state of the entity pipe and send a corresponding abnormal state signal to the edge service platform; the edge service platform is further configured to perform dynamic lightweight simulation analysis on the abnormal pipe corresponding to the abnormal state signal, and import a preliminary analysis scheme obtained by the analysis into the multi-field modeling analysis platform; the multi-field modeling analysis platform is further configured to, after obtaining element data and a model of the abnormal pipe corresponding to the preliminary analysis scheme, import the element data and the model of the abnormal pipe into the multi-modal fusion analysis engine, and perform modeling and analysis on the element data, the model and the preliminary analysis scheme of the abnormal pipe by the multi-modal fusion analysis engine to obtain a final solution scheme for the abnormal pipe.

[0011] Optionally, the pipe network system further comprises: a business platform configured to receive the abnormal state signal sent by the pipe entity perception system, determine the coordinates of the abnormal pipe where the abnormality occurs according to the abnormal state signal, and send an abnormal state modeling instruction to the multi-field modeling analysis platform; the multi-modal fusion analysis engine is further configured to, after obtaining the abnormal state modeling instruction, start modeling and analysis to obtain a final solution scheme for the abnormal pipe.

[0012] Optionally, the multi-field modeling analysis platform further comprises an algorithm library, a mechanism library and a scheme library, and the multi-modal fusion analysis engine is further configured to: retrieve a corresponding data analysis algorithm, a simulation mechanism model and a historical scheme in the algorithm library, the mechanism library and the scheme library according to the abnormal state modeling instruction, and perform modeling and analysis in combination with the preliminary analysis scheme to obtain a final solution scheme corresponding to the abnormal state signal.

[0013] Optionally, the pipe digital twin platform further comprises an integrated application development pool configured to obtain and display the final solution scheme.

[0014] Optionally, the multi-field modeling analysis platform is further configured to package the data corresponding to the abnormal state signal, the preliminary analysis scheme and the final solution scheme according to a preset format, and save the data, the preliminary analysis scheme and the final solution scheme packaged according to the preset format to the scheme library.

[0015] Optionally, the integrated application development pool comprises: secondary development of the business system, used for developing components corresponding to the application function requirements according to the application function requirements; micro-service component development, used for developing corresponding micro-service components for business sub-scenarios; scenario and model display, used for obtaining and dynamically displaying the final solution.

[0016] Optionally, the scenario and model display is also used for multi-dimensional and multi-scale digital display of the state and structure of the simulated pipeline of the entity pipeline.

[0017] Optionally, the pipeline entity perception system comprises a pipeline Internet of Things system, a SCADA system, an external system, and a pipeline automatic control system.

[0018] Optionally, the full-factor data model resource pool is also used for data cleaning, data compression, data smoothing, and data conversion processing on the stored data.

[0019] The second aspect of the application provides a pipeline data processing method, which comprises: obtaining and storing real-time state and behavior information of an entity pipeline; determining a target entity pipeline according to requirements; obtaining real-time factor data and models corresponding to the target entity pipeline, and modeling and analyzing and evaluating to determine a final solution for the target entity pipeline.

[0020] Optionally, the factor data comprises at least one of pipe body data, environmental data, fluid medium, equipment attribute, real-time operation data, and historical operation data of the entity pipeline.

[0021] Optionally, in the case of an abnormal condition occurring in the perceived entity pipeline system, the requirements are abnormal state analysis, and the method further comprises: obtaining an abnormal state signal of the entity pipeline system; performing dynamic lightweight simulation analysis on an abnormal pipeline corresponding to the abnormal state signal to obtain a preliminary analysis scheme; obtaining factor data and models of the abnormal pipeline corresponding to the preliminary analysis scheme; modeling and analyzing the abnormal state of the abnormal pipeline in combination with the preliminary analysis scheme to obtain a final solution.

[0022] Optionally, the dynamic lightweight simulation analysis on the abnormal pipeline corresponding to the abnormal state signal comprises: determining the coordinates of the abnormal pipeline; generating abnormal state modeling instructions corresponding to the abnormal state signal of the abnormal pipeline; modeling and analyzing the abnormal state of the abnormal pipeline according to the abnormal state modeling instructions.

[0023] Optionally, the modeling and analyzing of the abnormal state of the abnormal pipeline according to the abnormal state modeling instructions comprises: calling data analysis algorithms, simulation mechanism models, and historical schemes corresponding to the abnormal pipeline, and modeling and analyzing in combination with the preliminary analysis scheme to obtain a final solution for the abnormal state signal.

[0024] Optionally, the method further comprises: dynamically presenting the final solution.

[0025] Optionally, the method further comprises: encapsulating the data corresponding to the abnormal state signal, the preliminary analysis scheme and the final solution according to a preset format, and saving the encapsulated data, the preliminary analysis scheme and the final solution.

[0026] Optionally, in the case where the requirement is to perform simulation and analysis on the pipe network system, the target entity pipe is an entity pipe to be simulated and analyzed.

[0027] Optionally, the method further comprises: developing a component corresponding to the application function requirement according to the application function requirement; and / or developing a micro-service component corresponding to the business sub-scenario.

[0028] The third aspect of the present application provides a processor configured to execute the above-mentioned pipe data processing method.

[0029] The fourth aspect of the present application provides a pipe data processing apparatus comprising the above-mentioned processor.

[0030] The fifth aspect of the present application provides a machine-readable storage medium having instructions stored thereon, the instructions causing a processor to be configured to execute the above-mentioned pipe data processing method when executed by the processor.

[0031] The sixth aspect of the present application provides a computer program product comprising a computer program, wherein the computer program implements the above-mentioned pipe data processing method when executed by a processor.

[0032] The above-mentioned technical solution constructs a multi-modal fusion pipe network system with a pipe digital twin platform as the main carrier, provides a driving kernel for the pipe digital twin platform through a multi-field modeling analysis center, stores element data and models of the entity pipe in a full-factor data model resource pool, provides standardized data flow and unified models for the pipe digital twin, realizes dynamic mapping of the pipe entity and the pipe digital twin platform, and realizes lightweight and node deployment and operation of the pipe digital twin through deployment of an edge service platform.

[0033] Other features and advantages of the present application will be described in detail in the following specific embodiments. BRIEF DESCRIPTION OF DRAWINGS

[0034] The accompanying drawings are included to provide a further understanding of the present application, and constitute a part of the specification, and are used together with the following specific embodiments to explain the present application, but do not constitute a limitation on the present application. In the drawings:

[0035] Figure 1A structural block diagram of a pipeline digital twin platform of a pipe network system based on multi-modal fusion according to an embodiment of the present application is schematically shown;

[0036] Figure 2 A structural block diagram of a pipe network system based on multi-modal fusion according to an embodiment of the present application is schematically shown;

[0037] Figure 3 A flowchart of a pipeline data processing method according to an embodiment of the present application is schematically shown;

[0038] Figure 4 An internal structural diagram of a computer device according to an embodiment of the present application is schematically shown. DETAILED DESCRIPTION

[0039] To make the objectives, technical solutions, and advantages of the embodiments of the present application clearer, the technical solutions in the embodiments of the present application will be described clearly and completely below with reference to the drawings in the embodiments of the present application. It should be understood that the specific implementation manners described herein are only used to explain and illustrate the embodiments of the present application and should not be used to limit the embodiments of the present application. Based on the embodiments in the present application, all other embodiments obtained by a person of ordinary skill in the art without creative work fall within the scope of protection of the present application.

[0040] In one embodiment, a pipe network system based on multi-modal fusion is provided, and the pipe network system includes a pipeline digital twin platform, as shown in Figure 1 The pipeline digital twin platform includes an edge service platform, a full-element data model resource pool, and a multi-field modeling and analysis middle station, wherein:

[0041] The edge service platform 101 is configured to acquire real-time state and behavior information of an entity pipeline and import the real-time state and behavior information into the full-element data model resource pool.

[0042] The full-element data model resource pool 102 is configured to store element data and models of the entity pipeline and update and optimize the stored element data and models according to the real-time state and behavior information imported by the edge service platform.

[0043] The multi-field modeling and analysis middle station 103 includes a multi-modal fusion analysis engine, and is configured to determine a target entity pipeline according to a demand, import real-time element data and models of the target entity pipeline acquired through the full-element data model resource pool into the multi-modal fusion analysis engine, model and analyze and evaluate the real-time element data and models of the target entity pipeline through the multi-modal fusion analysis engine, and determine a final solution for the target entity pipeline.

[0044] The pipeline digital twin can be provided with a carrier environment by constructing a pipeline digital twin platform. The pipeline digital twin platform can include an edge service platform 101. The edge service platform 101 can acquire real-time state and behavior information of the entity pipeline. The real-time state and behavior information of the entity pipeline can include, for example, pipeline transportation operating conditions, device operating states, pipe body structure and protection states, and pipeline laying environment states. Specifically, for example, the pipeline transportation operating conditions can include the pressure, flow, temperature, etc. of the transported medium. The device operating states can include device vibration parameters, temperature monitoring parameters, compressor operating state parameters, pump operating state parameters, etc. The pipe body structure and protection state can include cathode protection potential, stress and strain change, environmental corrosion, weld state information, etc. The pipeline laying environment state can include pipeline wind force of crossing section, buried pipeline mountain state, frozen soil / desert geomechanics state, river state, etc. After acquiring the real-time state and behavior information of the entity pipeline, the edge service platform 101 can import the real-time state and behavior information into a full-element data model resource pool 102.

[0045] The full-element data model resource pool 102 can store element data and models of the entity pipeline. In one embodiment, the element data of the entity pipeline can include at least one of pipe body data, environmental data, fluid medium, device attributes, real-time operating data, and historical operating data of the entity pipeline. In one embodiment, the full-element data model resource pool is also used for data cleaning, data compression, data smoothing, and data conversion processing of the stored data. That is, the full-element data model resource pool 102 can also perform data processing on the stored element data of the entity pipeline, and the data processing process can include data cleaning, data compression, data smoothing, and data conversion processing. In addition, the full-element data model resource pool 102 can also update and optimize the stored element data and models according to the real-time state and behavior information imported by the edge service platform 101.

[0046] The multi-field modeling analysis station 103 can determine a target entity pipeline according to a requirement, import real-time element data and models of the target entity pipeline obtained from the full-element data model resource pool into the multi-modal fusion analysis engine. The multi-modal fusion analysis engine can model and analyze the real-time element data and models of the target entity pipeline to determine a final solution for the target entity pipeline. In an embodiment, the multi-modal fusion analysis engine includes a data analysis engine and a multi-physical field simulation engine. The data analysis engine includes a plurality of analysis functions and tools corresponding to each analysis function. The analysis functions include at least one of a data mining function, a data statistical function, and a machine learning function. The multi-physical field simulation engine includes at least one of a modeling engine function, a map engine function, and a model management function. The data analysis engine and the multi-physical field simulation engine can construct an application service or a decision analysis model, and can simulate and analyze an application scenario.

[0047] The above technical solution constructs a multi-modal fusion pipeline system with a pipeline digital twin platform as the main carrier. The multi-field modeling analysis station provides a driving kernel for the pipeline digital twin platform, stores element data and models of the entity pipeline based on the full-element data model resource pool, provides standardized data flow and unified models for the pipeline digital twin, realizes dynamic mapping between the pipeline entity and the pipeline digital twin platform, and realizes lightweight and node deployment and operation of the pipeline digital twin by deploying an edge service platform.

[0048] In an embodiment, the pipeline system further includes a pipeline entity perception system connected to the entity pipeline, configured to perceive abnormal states of the entity pipeline and send corresponding abnormal state signals to the edge service platform; the edge service platform is further configured to perform dynamic lightweight simulation analysis on the abnormal pipeline corresponding to the abnormal state signal, and import a preliminary analysis scheme obtained by the analysis into the multi-field modeling analysis station; the multi-field modeling analysis station is further configured to import element data and models of the abnormal pipeline into the multi-modal fusion analysis engine after obtaining the element data and models of the abnormal pipeline corresponding to the preliminary analysis scheme, and perform modeling and analysis on the element data, models, and preliminary analysis scheme of the abnormal pipeline by the multi-modal fusion analysis engine to obtain a final solution for the abnormal pipeline.

[0049] In an embodiment, the pipeline system further includes a business platform configured to receive the abnormal state signals sent by the pipeline entity perception system, determine the coordinates of the abnormal pipeline where the abnormality occurs according to the abnormal state signals, and send an abnormal state modeling instruction to the multi-field modeling analysis station; the multi-modal fusion analysis engine is further configured to start modeling and analysis to obtain a final solution for the abnormal pipeline after obtaining the abnormal state modeling instruction.

[0050] In one embodiment, the multi-domain modeling analysis platform further comprises an algorithm library, a mechanism library and a scheme library, and the multi-modal fusion analysis engine is further configured to: according to the abnormal state modeling instruction, call the corresponding data analysis algorithm, simulation mechanism model and historical scheme in the algorithm library, mechanism library and scheme library, and combine the preliminary analysis scheme to perform modeling and analysis, so as to obtain the final solution corresponding to the abnormal state signal.

[0051] The edge service platform 101 can be connected with a pipeline entity perception system, and the pipeline entity perception system can be connected with a physical pipeline. In one embodiment, the pipeline entity perception system comprises a pipeline Internet of Things system, a SCADA system, an external system and a pipeline automatic control system. In addition, the pipeline entity perception system can further comprise a cloud design platform. The cloud design platform can refer to a pipeline construction period platform, which can establish and manage various pipeline data and models in the static digital twin of the pipeline construction period. After the pipeline construction is completed, the cloud design platform can transfer the required data and models of the static digital twin to the operation unit for use.

[0052] When the physical pipeline is in an abnormal state, the pipeline entity perception system can perceive the abnormal state of the physical pipeline. The abnormal state can be an abnormality of the physical pipeline itself. For example, corrosion of the physical pipeline body, failure of the corrosion protection layer, defects of the pipeline body and weld, non-uniform settlement of the pipeline, third-party construction, leakage, explosion, etc. The abnormal state can also be an abnormality of the equipment monitoring the physical pipeline. For example, abnormal monitoring data and abnormal working conditions of compressors, valves, pumps, flow meters, etc. The abnormal state can also be an abnormality of the environment around the physical pipeline. For example, landslides, earthquakes, goaf collapse, floods, etc. in the environment around the laid pipeline. The abnormal state can also refer to an abnormality of the conveying medium in the physical pipeline. For example, abnormal temperature of oil products entering and leaving the station, change of product oil components, high water content of natural gas, abnormal fluctuation of conveying pressure / flow, etc. When the pipeline entity perception system perceives the abnormal state of the physical pipeline, the pipeline entity perception system can send the corresponding abnormal state signal to the edge service platform 101. After the edge service platform 101 obtains the abnormal state signal of the physical pipeline, the edge service platform 101 can perform dynamic lightweight simulation analysis on the abnormal pipeline corresponding to the abnormal state signal, and import the preliminary analysis scheme obtained by the analysis into the multi-domain modeling analysis platform 103. That is, the edge service platform 101 can be connected with the multi-domain modeling analysis platform 103.

[0053] After importing the preliminary analysis scheme obtained by analysis into the multi-domain modeling and analysis platform 103, the multi-domain modeling and analysis platform 103 can obtain the element data and model of the abnormal pipeline corresponding to the preliminary analysis scheme. Then, the multi-domain modeling and analysis platform 103 can import the element data and model of the abnormal pipeline into the multi-modal fusion analysis engine. Through the multi-modal fusion analysis engine, modeling and analysis are performed on the element data, model and preliminary analysis scheme of the abnormal pipeline to obtain the final solution for the abnormal pipeline.

[0054] The pipeline network system can include a business platform. The business platform can include a pipeline engineering construction application platform, a pipeline production regulation application platform, a pipeline integrity application platform, and a device management application platform, etc. When the pipeline entity perception system perceives the abnormal real-time state and abnormal behavior information of the entity pipeline, the pipeline entity perception system can send an abnormal state signal to the business platform. When the business platform receives the abnormal state signal sent by the pipeline entity perception system, it can determine the coordinates of the abnormal pipeline where the abnormality occurs according to the abnormal state signal, and issue an abnormal state modeling instruction to the multi-domain modeling and analysis platform 103. When the multi-modal fusion analysis engine of the multi-domain modeling and analysis platform 103 obtains the abnormal state modeling instruction, modeling and analysis can be started to obtain the final solution for the abnormal pipeline. Specifically, the multi-domain modeling and analysis platform also includes an algorithm library, a mechanism library and a scheme library. Therefore, when the multi-modal fusion analysis engine starts modeling and analysis, the corresponding data analysis algorithm, simulation mechanism model and historical scheme in the algorithm library, mechanism library and scheme library can be called according to the abnormal state modeling instruction. At the same time, the multi-modal fusion analysis engine can also model and analyze in combination with the preliminary analysis scheme to obtain the final solution corresponding to the abnormal state signal.

[0055] In one embodiment, the pipeline digital twin platform further includes an integrated application development pool for obtaining and displaying the final solution.

[0056] In one embodiment, the integrated application development pool includes: secondary development of a business system for developing components corresponding to application function requirements according to application function requirements; micro-service component development for developing corresponding micro-service components for business sub-scenarios; scene and model display for obtaining and dynamically displaying the final solution.

[0057] In one embodiment, the scene and model display is also used for multi-dimensional and multi-scale digital display of the state and structure of the simulated pipeline of the entity pipeline.

[0058] The pipeline digital twin platform may include an integrated application development pool. Further, the integrated application development pool may include secondary development of business systems, microservice component development, and scenario and model demonstrations. Specifically, secondary development of business systems can develop components corresponding to application functional requirements. Microservice component development can develop corresponding microservice components for business sub-scenarios. Scenario and model demonstrations can acquire and dynamically display the final solution. Therefore, given a determined final solution for the target entity pipeline, the integrated application development pool can acquire and display the final solution. Specifically, the scenario and model demonstrations in the integrated application development pool can provide a multi-dimensional and multi-scale digital display of the simulated pipeline's state and structure.

[0059] In one embodiment, the multi-domain modeling and analysis platform is also used to encapsulate the data corresponding to the abnormal state signal, the preliminary analysis plan and the final solution according to a preset format, and save the data, the preliminary analysis plan and the final solution encapsulated according to the preset format to the solution library.

[0060] Once the final solution for the target entity pipeline is determined, the multi-domain modeling and analysis platform 103 can encapsulate the data corresponding to the abnormal state signals, the preliminary analysis plan, and the final solution according to a preset format. This encapsulated data, preliminary analysis plan, and final solution are then saved to a solution library for future reference. The pre-set format encapsulation can be tailored to specific scenario requirements or business platform needs, allowing for output of results through app encapsulation, micro-component development, system push notifications, entity feedback, or other methods.

[0061] In one embodiment, such as Figure 2 As shown, a schematic diagram of a pipeline network system based on multimodal fusion is provided. Figure 2 The pipeline network system shown can include a pipeline network system digital twin platform, a pipeline entity perception system, and a business platform.

[0062] The pipeline network system digital twin platform can include an integrated application development pool, a multi-field comprehensive modeling analysis platform, an edge service platform, and a full-factor data model resource pool. The integrated application development pool can include business system secondary development, scene and model display, micro-service component development business scenarios, and training and exercises. The integrated application development pool can be connected to the multi-field comprehensive modeling analysis platform. The multi-field comprehensive modeling analysis platform can include a multi-modal fusion analysis engine, an algorithm library, a mechanism library, and a scheme library. The multi-modal fusion analysis engine is connected to the algorithm library, the mechanism library, and the scheme library. The multi-modal fusion analysis engine can include a data analysis engine and a multi-physical field simulation engine. The data analysis engine can include a plurality of analysis functions and tools corresponding to each analysis function, wherein the analysis functions can include data mining functions, data statistical functions, and machine learning functions. The multi-physical field simulation engine includes a modeling engine function, a map engine function, and a model management function. The multi-field comprehensive modeling analysis platform can be connected to the edge service platform. The edge service platform can include edge computing functions, real-time data functions, lightweight model functions, and node data functions. The edge service platform can be connected to the full-factor data model resource pool, which can include pipe body data models, environmental data models, flowing media, and equipment parameter models. The full-factor data model resource pool can be connected to the multi-field comprehensive modeling analysis platform, and the full-factor data model resource pool can also include data cleaning functions, data compression functions, data smoothing functions, and data conversion functions.

[0063] The pipeline entity perception system can include a pipeline Internet of Things system, a SCADA system, an external system, a cloud design platform, and a pipeline automatic control system. The pipeline entity perception system can be connected to the edge service platform and the full-factor data model resource pool in the pipeline network system digital twin platform. The pipeline entity perception system can also be connected to a business platform.

[0064] The business platform can include a pipeline engineering construction application platform, a pipeline production regulation application platform, a pipeline integrity application platform, and a device management application platform. The pipeline engineering construction application platform can integrate and manage engineering business such as pipeline construction period design and construction, and can manage various types of engineering construction data. The pipeline production regulation application platform can realize functions such as transportation scheduling, pipeline operation state monitoring, pipeline device remote control, pipeline operation online / offline simulation, and process optimization through pipelines of different media such as natural gas, crude oil, and refined oil. The pipeline integrity application platform can manage and maintain pipeline physical assets, which can include pipeline bodies, device operation and maintenance related data, and models. The device management application platform can monitor, manage, and maintain various types of data such as the operation, maintenance, and repair of devices such as compressors, valves, pumps, and flow devices involved in the pipeline. The business platform can be connected to the integrated application development pool and the multi-field comprehensive modeling platform in the pipeline network system digital twin platform.

[0065] The above technical solution constructs a multi-modal fusion pipeline network system with a pipeline digital twin platform as the main carrier, relies on an edge service platform, a multi-field modeling and analysis middle platform, a full-factor data model resource pool, an integrated application development pool, and a business platform, connects the information channel formed by the sensing system in the physical pipeline, constructs a pipeline digital twin platform with unified pipeline business chain data and model standards, and a pipeline digital twin multi-modal analysis kernel, and provides integrated and refined decision support for pipeline operation management.

[0066] Figure 3 A flowchart of a pipeline data processing method according to an embodiment of the present application is schematically shown. As shown in Figure 3 In an embodiment of the present application, a pipeline data processing method is provided, including the following steps:

[0067] Step 301, acquiring real-time state and behavior information of the physical pipeline and storing.

[0068] Step 302, determining a target physical pipeline according to requirements.

[0069] Step 203, acquiring real-time factor data and models corresponding to the target physical pipeline, and modeling and analyzing and evaluating to determine the final solution for the target physical pipeline.

[0070] The processor can acquire and store real-time state and behavior information of the entity pipeline. After acquiring the real-time state and behavior information of the entity pipeline, the processor can determine a target entity pipeline according to a requirement. In an embodiment, in a case where the requirement is to perform a simulation exercise analysis on the pipe network system, the target entity pipeline is an entity pipeline to be subjected to the simulation exercise analysis. The requirement can be to perform a simulation exercise analysis on the pipe network system. In a case where the pipe network system is subjected to the simulation exercise analysis, the determined target entity pipeline can be an entity pipeline to be subjected to the simulation exercise analysis.

[0071] In a case where the target entity pipeline is determined, the processor can acquire real-time element data and models corresponding to the target entity pipeline. In an embodiment, the element data includes pipe body data, environmental data, fluid medium, equipment attributes, real-time operation data, and historical operation data of the entity pipeline. That is, the processor can acquire real-time pipe body data, environmental data, fluid medium, equipment attributes, real-time operation data, and historical operation data corresponding to the target entity pipeline. In a case where the real-time element data and models corresponding to the target entity pipeline are acquired, the processor can perform modeling and analysis evaluation to determine a final solution for the target entity pipeline.

[0072] In a case where an abnormal condition of the perceived entity pipe network system occurs, the abnormal state can be analyzed. According to a requirement of the abnormal state analysis, the processor can determine a target entity pipeline. In an embodiment, in a case where an abnormal condition of the perceived entity pipe network system occurs, the requirement is the abnormal state analysis, and the method further includes: acquiring an abnormal state signal of the entity pipe network system; performing dynamic lightweight simulation analysis on an abnormal pipeline corresponding to the abnormal state signal to obtain a preliminary analysis scheme; acquiring element data and models of the abnormal pipeline corresponding to the preliminary analysis scheme; and modeling and analyzing the abnormal state of the abnormal pipeline in combination with the preliminary analysis scheme to obtain a final solution.

[0073] The processor can first acquire the abnormal state signal of the entity pipe network system, and then can perform dynamic lightweight simulation analysis on the abnormal pipeline corresponding to the abnormal state signal to obtain a preliminary analysis scheme. In an embodiment, the dynamic lightweight simulation analysis on the abnormal pipeline corresponding to the abnormal state signal comprises: determining the coordinates where the abnormal pipeline is located; generating corresponding abnormal state modeling instructions according to the abnormal state signal of the abnormal pipeline; modeling and analyzing the abnormal state of the abnormal pipeline according to the abnormal state modeling instructions. The processor can first determine the coordinates where the abnormal pipeline is located. Then, the processor can generate corresponding abnormal state modeling instructions according to the abnormal state signal of the abnormal pipeline. According to the abnormal state modeling instructions, the processor can model and analyze the abnormal state of the abnormal pipeline. In an embodiment, modeling and analyzing the abnormal state of the abnormal pipeline according to the abnormal state modeling instructions comprises: calling the data analysis algorithm, the simulation mechanism model and the historical scheme corresponding to the abnormal pipeline, and modeling and analyzing in combination with the preliminary analysis scheme to obtain a final solution scheme for the abnormal state signal. In modeling and analyzing the abnormal state, the processor can first call the data analysis algorithm, the simulation mechanism model and the historical scheme corresponding to the abnormal pipeline, and model and analyze in combination with the preliminary analysis scheme to obtain a final solution scheme for the abnormal state signal.

[0074] In an embodiment, the method further comprises: dynamically displaying the final solution scheme.

[0075] In an embodiment, the method further comprises: packaging the data corresponding to the abnormal state signal, the preliminary analysis scheme and the final solution scheme according to a preset format, and saving the packaged data, the preliminary analysis scheme and the final solution scheme.

[0076] In the case where the final solution scheme is acquired, the processor can dynamically display the final solution scheme. Specifically, the processor can package the data corresponding to the abnormal state signal, the preliminary analysis scheme and the final solution scheme according to a preset format, and save the packaged data, the preliminary analysis scheme and the final solution scheme.

[0077] In an embodiment, the method further comprises: developing a component corresponding to an application function requirement according to the application function requirement; and / or developing a micro-service component corresponding to a business sub-scene.

[0078] In the case where the final solution scheme is acquired, the processor can also develop a component corresponding to an application function requirement according to the application function requirement. The processor can also develop a micro-service component corresponding to a business sub-scene.

[0079] The above technical solution improves the efficiency of pipeline data processing by acquiring real-time status and behavior information of physical pipelines, and can also quickly determine the final solution for physical pipelines, providing significant technical support for the normal operation of physical pipelines.

[0080] Figure 3 This is a flowchart illustrating a pipeline data processing method in one embodiment. It should be understood that, although... Figure 3 The steps in the flowchart are shown sequentially as indicated by the arrows, but these steps are not necessarily executed in the order indicated by the arrows. Unless otherwise specified herein, there is no strict order in which these steps are executed, and they can be performed in other orders. Figure 3 At least some of the steps in the process may include multiple sub-steps or multiple stages. These sub-steps or stages are not necessarily completed at the same time, but can be executed at different times. The execution order of these sub-steps or stages is not necessarily sequential, but can be executed in turn or alternately with other steps or at least some of the sub-steps or stages of other steps.

[0081] In one embodiment, a pipeline data processing apparatus is provided, the pipeline data processing apparatus including a processor.

[0082] This application provides a storage medium storing a program that, when executed by a processor, implements the above-described pipeline data processing method.

[0083] This application provides a processor for running a program, wherein the program executes the above-described pipeline data processing method during runtime.

[0084] In one embodiment, a computer device is provided, which may be a server, and its internal structure diagram may be as follows: Figure 4 As shown, the computer device includes a processor A01, a network interface A02, memory (not shown), and a database (not shown) connected via a system bus. The processor A01 provides computing and control capabilities. The memory includes internal memory A03 and a non-volatile storage medium A04. The non-volatile storage medium A04 stores an operating system B01, a computer program B02, and a database (not shown). The internal memory A03 provides an environment for the operation of the operating system B01 and the computer program B02 stored in the non-volatile storage medium A04. The database stores real-time status and behavioral information data of the physical pipeline. The network interface A02 communicates with external terminals via a network connection. When the computer program B02 is executed by the processor A01, it implements a pipeline data processing method.

[0085] Those skilled in the art can understand that Figure 4 The structure shown in the figure is only a block diagram of part of the structure related to the scheme of the present application, and does not constitute a limitation on the computer device to which the scheme of the present application is applied. The specific computer device can include more or fewer components than those shown in the figure, or combine certain components, or have a different arrangement of components.

[0086] In one embodiment, the pipeline data processing apparatus provided by the present application can be implemented in the form of a computer program, which can run on a computer device as shown in the figure. Figure 4

[0087] The embodiment of the present application provides a device, which comprises a processor, a memory and a program stored on the memory and executable on the processor. When the processor executes the program, the following steps are implemented: acquiring real-time state and behavior information of an entity pipeline and storing; determining a target entity pipeline according to a demand; acquiring real-time element data and a model corresponding to the target entity pipeline, and modeling and analyzing and evaluating to determine a final solution for the target entity pipeline.

[0088] In one embodiment, the element data includes at least one of pipe body data, environmental data, fluid medium, equipment attribute, real-time running data and historical running data of the entity pipeline.

[0089] In one embodiment, in the case of perceiving an abnormal condition occurring in the entity pipeline network system, the demand is abnormal state analysis, and the method further comprises: acquiring an abnormal state signal of the entity pipeline network system; performing dynamic lightweight simulation analysis on an abnormal pipeline corresponding to the abnormal state signal to obtain a preliminary analysis scheme; acquiring element data and a model of the abnormal pipeline corresponding to the preliminary analysis scheme; modeling and analyzing the abnormal state of the abnormal pipeline in combination with the preliminary analysis scheme to obtain a final solution.

[0090] In one embodiment, the dynamic lightweight simulation analysis on the abnormal pipeline corresponding to the abnormal state signal comprises: determining a coordinate where the abnormal pipeline is located; generating an abnormal state modeling instruction corresponding to the abnormal pipeline according to the abnormal state signal of the abnormal pipeline; modeling and analyzing the abnormal state of the abnormal pipeline according to the abnormal state modeling instruction.

[0091] In one embodiment, the modeling and analyzing the abnormal state of the abnormal pipeline according to the abnormal state modeling instruction comprises: calling a data analysis algorithm, a simulation mechanism model and a historical scheme corresponding to the abnormal pipeline, and modeling and analyzing in combination with the preliminary analysis scheme to obtain a final solution for the abnormal state signal.

[0092] In one embodiment, the method further comprises: dynamically displaying the final solution. ​

[0093] In an embodiment, the method further comprises: encapsulating the data corresponding to the abnormal state signal, the preliminary analysis scheme and the final solution in a preset format, and saving the encapsulated data, the preliminary analysis scheme and the final solution.

[0094] In an embodiment, when the requirement is to perform simulation analysis on the pipe network system, the target entity pipe is an entity pipe to be simulated and analyzed.

[0095] In an embodiment, the method further comprises: developing a component corresponding to the application function requirement according to the application function requirement; and / or developing a micro-service component corresponding to the business sub-scenario.

[0096] The application also provides a computer program product adapted to execute the program of the following method steps when executed on a data processing device: obtaining real-time state and behavior information of an entity pipe and storing; determining a target entity pipe according to a requirement; obtaining real-time element data and models corresponding to the target entity pipe, and modeling and analyzing and evaluating to determine a final solution for the target entity pipe.

[0097] In an embodiment, the element data includes at least one of pipe body data, environmental data, fluid medium, device attribute, real-time running data, and historical running data of the entity pipe.

[0098] In an embodiment, when an abnormal condition occurs in the entity pipe network system, the requirement is abnormal state analysis, and the method further comprises: obtaining an abnormal state signal of the entity pipe network system; performing dynamic lightweight simulation analysis on an abnormal pipe corresponding to the abnormal state signal to obtain a preliminary analysis scheme; obtaining element data and models of the abnormal pipe corresponding to the preliminary analysis scheme; modeling and analyzing the abnormal state of the abnormal pipe in combination with the preliminary analysis scheme to obtain a final solution.

[0099] In an embodiment, the dynamic lightweight simulation analysis on the abnormal pipe corresponding to the abnormal state signal comprises: determining the coordinates of the abnormal pipe; generating an abnormal state modeling instruction corresponding to the abnormal state signal of the abnormal pipe; modeling and analyzing the abnormal state of the abnormal pipe according to the abnormal state modeling instruction.

[0100] In an embodiment, the modeling and analyzing the abnormal state of the abnormal pipe according to the abnormal state modeling instruction comprises: calling a data analysis algorithm, a simulation mechanism model and a historical scheme corresponding to the abnormal pipe, and modeling and analyzing in combination with the preliminary analysis scheme to obtain a final solution for the abnormal state signal.

[0101] In an embodiment, the method further comprises: dynamically displaying the final solution.

[0102] In an embodiment, the method further includes: encapsulating the data corresponding to the abnormal state signal, the preliminary analysis scheme, and the final solution according to a preset format, and saving the encapsulated data, the preliminary analysis scheme, and the final solution.

[0103] In an embodiment, when the requirement is to perform simulation analysis on the pipe network system, the target entity pipe is an entity pipe to be subjected to simulation analysis.

[0104] In an embodiment, the method further includes: developing a component corresponding to the application function requirement according to the application function requirement; and / or developing a micro-service component corresponding to the business sub-scenario.

[0105] Those skilled in the art should understand that embodiments of the present application can be provided as a method, a system, or a computer program product. Therefore, the present application can take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment combining software and hardware aspects. Moreover, the present application can take the form of a computer program product implemented on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROMs, optical storage devices, etc.) containing computer-usable program code.

[0106] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to embodiments of the present application. It should be understood that each flow and / or block in the flowcharts and / or block diagrams, as well as combinations of flows and / or blocks in the flowcharts and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing apparatus to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing apparatus generate an apparatus for implementing the functions specified in the flowcharts and / or block diagrams. Figure 1 The flowcharts and / or block diagrams can include one or more flows and / or blocks that implement the functions specified in the flowcharts and / or block diagrams. Figure 1 The flowcharts and / or block diagrams can include one or more flows and / or blocks that implement the functions specified in the flowcharts and / or block diagrams.

[0107] These computer program instructions can also be stored in a computer-readable memory that can direct the computer or other programmable data processing apparatus to work in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture including an instruction apparatus that implements the functions specified in the flowcharts and / or block diagrams. Figure 1 The flowcharts and / or block diagrams can include one or more flows and / or blocks that implement the functions specified in the flowcharts and / or block diagrams. Figure 1 The flowcharts and / or block diagrams can include one or more flows and / or blocks that implement the functions specified in the flowcharts and / or block diagrams.

[0108] ​​​​​​​​​​​​​​​​​These computer program instructions can also be loaded into 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 such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart block or blocks. Figure 1 Figure 1

[0109] In one typical configuration, the computing device includes one or more processors (CPUs), input / output interfaces, network interfaces, and memory.

[0110] The memory can include non-persistent memory and / or volatile memory, such as random access memory (RAM) about which the processor can execute instructions. The memory can also include non-volatile memory, such as read only memory (ROM), electrically programmable read only memory (EPROM), electrically erasable programmable read only memory (EEPROM), programmable read only memory (PROM), erasable programmable read only memory (EPROM), flash memory, or a combination of non-volatile memories in different types. The memory can also include a compact disk read only memory (CD-ROM), digital versatile disk (DVD), Blu-ray, or another non-transitory computer readable medium, which is non-volatile and non-transitory in nature, about which at least some of the instructions executable by the processor are stored. The memory is an example of a computer readable medium.

[0111] Computer readable media includes permanent and non-permanent, removable and non-removable media implemented in any method or technology for storage of information such as computer readable instructions, data structures, program modules 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 programmable read only memory (EEPROM), flash memory or other memory technology, compact disk read only memory (CD-ROM), digital versatile disk (DVD), or other optical storage, magnetic cassette, magnetic tape, magnetic disk storage or other magnetic storage devices, or any other non-transmission medium that can be used to store information accessible to a computing device. According to the definition herein, computer readable media does not include transitory computer readable media, such as modulated data signals and carrier waves.

[0112] It should also be noted that the terms "comprising", "containing", or any other variant thereof are intended to encompass a non-exclusive inclusion, such that a process, method, article or apparatus that comprises a list of elements does not include only those elements recited, but can also include other elements not expressly listed or inherent to such process, method, article or apparatus. Without more limitations, the element defined by the statement "comprising a" does not exclude the presence of additional identical elements in the process, method, article or apparatus including the element.

[0113] ​​The above merely provides an example of the present application, and is not intended to limit the present application. For those skilled in the art, the present application can have various modifications and changes. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principle of the present application shall fall into the scope of claims of the present application.

Claims

1. A pipeline network system based on multimodal fusion, characterized in that, The pipeline network system includes: a pipeline digital twin platform, comprising: An edge service platform is used to acquire real-time status and behavior information of physical pipelines and import the real-time status and behavior information into a full-element data model resource pool. The full-element data model resource pool is used to store the element data and model of the entity pipeline, and to update and optimize the stored element data and model according to the real-time status and behavior information imported by the edge service platform. A multi-domain modeling and analysis platform, including a multi-modal fusion analysis engine, is used to determine the target entity pipeline according to requirements. The platform imports the real-time element data and model of the target entity pipeline obtained through the full-element data model resource pool into the multi-modal fusion analysis engine. The multi-modal fusion analysis engine models and analyzes and evaluates the real-time element data and model of the target entity pipeline to determine the final solution for the target entity pipeline. The element data includes at least one of the following: pipe body data of the physical pipeline, environmental data, fluid medium, equipment attributes, real-time operation data, and historical operation data; The multimodal fusion analysis engine includes a data analysis engine and a multiphysics simulation engine. The data analysis engine includes multiple analysis functions and tools corresponding to each analysis function. The analysis functions include at least one of data mining, data statistics, and machine learning functions. The multiphysics simulation engine includes at least one of modeling engine, mapping engine, and model management functions. The pipeline system also includes: The pipeline entity sensing system is connected to the physical pipeline and is used to sense abnormal states occurring in the physical pipeline and send corresponding abnormal state signals to the edge service platform. The edge service platform is also used to perform dynamic lightweight simulation analysis on the abnormal pipelines corresponding to the abnormal state signals, and import the preliminary analysis scheme obtained from the analysis into the multi-domain modeling and analysis platform. The multi-domain modeling and analysis platform is also used to import the element data and model of the abnormal pipeline corresponding to the preliminary analysis plan into the multimodal fusion analysis engine after obtaining the element data and model of the abnormal pipeline. The multimodal fusion analysis engine combines the element data and model of the abnormal pipeline with the preliminary analysis plan to perform modeling and analysis, so as to obtain the final solution for the abnormal pipeline.

2. The pipeline network system based on multimodal fusion according to claim 1, characterized in that, The pipeline system also includes: The business platform is used to receive abnormal status signals sent by the pipeline entity perception system, determine the coordinates of the abnormal pipeline where the abnormality occurred based on the abnormal status signals, and send abnormal status modeling instructions to the multi-domain modeling and analysis platform. The multimodal fusion analysis engine is also used to initiate modeling and analysis after receiving the abnormal state modeling instruction, so as to obtain the final solution for the abnormal pipeline.

3. The pipeline network system based on multimodal fusion according to claim 2, characterized in that, The multi-domain modeling and analysis platform also includes an algorithm library, a mechanism library, and a solution library. The multimodal fusion analysis engine is also used for: According to the abnormal state modeling instruction, the corresponding data analysis algorithm, simulation mechanism model and historical solution are retrieved from the algorithm library, mechanism library and solution library, and modeled and analyzed in combination with the preliminary analysis solution to obtain the final solution corresponding to the abnormal state signal.

4. The pipeline network system based on multimodal fusion according to any one of claims 1 to 3, characterized in that, The pipeline digital twin platform also includes an integrated application development pool for acquiring and displaying the final solution.

5. The pipeline network system based on multimodal fusion according to claim 4, characterized in that, The multi-domain modeling and analysis platform is also used to encapsulate the data corresponding to the abnormal state signal, the preliminary analysis scheme, and the final solution according to a preset format, and save the encapsulated data, the preliminary analysis scheme, and the final solution to the solution library.

6. The pipeline network system based on multimodal fusion according to claim 4, characterized in that, The integrated application development pool includes: Secondary development of the business system is used to develop components corresponding to the application functional requirements based on the application functional requirements. Microservice component development is used to develop corresponding microservice components for specific business sub-scenarios. Scene and model display, used to obtain and dynamically display the final solution.

7. The pipeline network system based on multimodal fusion according to claim 6, characterized in that, The scene and model display is also used to digitally display the state and structure of the simulated pipeline of the physical pipeline in a multi-dimensional and multi-scale manner.

8. The pipeline network system based on multimodal fusion according to claim 1, characterized in that, The pipeline entity sensing system includes a pipeline Internet of Things system, a SCADA system, an external system, and a pipeline automatic control system.

9. The pipeline network system based on multimodal fusion according to claim 1, characterized in that, The full-element data model resource pool is also used for data cleaning, data compression, data smoothing, and data transformation of the stored data.

10. A pipeline data processing method, characterized in that, Applied to the pipeline network system based on multimodal fusion as described in any one of claims 1-9, the method comprises: Acquire and store real-time status and behavior information of the physical pipeline; Determine the target physical pipeline based on requirements; Acquire real-time element data and models corresponding to the target entity pipeline, and perform modeling, analysis and evaluation to determine the final solution for the target entity pipeline; The element data includes at least one of the following: pipe body data of the physical pipeline, environmental data, fluid medium, equipment attributes, real-time operation data, and historical operation data; In the case of an abnormal situation occurring in the perceived physical pipeline network system, the requirement is abnormal state analysis, and the method further includes: Obtain the abnormal status signal of the physical pipeline network system; Dynamic lightweight simulation analysis is performed on the abnormal pipeline corresponding to the abnormal state signal to obtain a preliminary analysis scheme; Obtain the element data and model of the abnormal pipeline corresponding to the preliminary analysis plan; The abnormal state of the abnormal pipeline is modeled and analyzed in conjunction with the preliminary analysis scheme to obtain a final solution.

11. The pipeline data processing method according to claim 10, characterized in that, The dynamic lightweight simulation analysis of the abnormal pipeline corresponding to the abnormal state signal includes: Determine the coordinates of the abnormal pipeline; Generate corresponding abnormal state modeling instructions based on the abnormal state signals of the abnormal pipeline; The abnormal state of the abnormal pipeline is modeled and analyzed according to the abnormal state modeling instructions.

12. The pipeline data processing method according to claim 11, characterized in that, The step of modeling and analyzing the abnormal state of the abnormal pipeline according to the abnormal state modeling instruction includes: The data analysis algorithm, simulation mechanism model, and historical solutions corresponding to the abnormal pipeline are retrieved and combined with the preliminary analysis scheme to model and analyze, so as to obtain the final solution for the abnormal state signal.

13. The pipeline data processing method according to any one of claims 10 to 12, characterized in that, The method also includes: dynamically displaying the final solution.

14. The pipeline data processing method according to claim 13, characterized in that, The method further includes: The data corresponding to the abnormal state signal, the preliminary analysis plan, and the final solution are packaged according to a preset format, and the packaged data, preliminary analysis plan, and final solution are saved.

15. The pipeline data processing method according to claim 10, characterized in that, When the requirement is to conduct simulation and analysis of the pipeline network system, the target physical pipeline is the physical pipeline to be simulated and analyzed.

16. The pipeline data processing method according to claim 10, characterized in that, The method further includes: Based on the application's functional requirements, develop components corresponding to those requirements; and / or develop corresponding microservice components for specific business sub-scenarios.

17. A processor, characterized in that, It is configured to perform the pipeline data processing method according to any one of claims 10 to 16.

18. A pipeline data processing device, characterized in that, Includes the processor as described in claim 17.

19. A machine-readable storage medium storing instructions thereon, characterized in that, When executed by a processor, this instruction causes the processor to be configured to perform the pipeline data processing method according to any one of claims 10 to 16.

20. A computer program product, comprising a computer program, characterized in that, When the computer program is executed by a processor, it implements the pipeline data processing method according to any one of claims 10 to 16.

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