CN111307055A - Design method of pipeline digital twin system - Google Patents
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- CN111307055A CN111307055A CN202010138601.4A CN202010138601A CN111307055A CN 111307055 A CN111307055 A CN 111307055A CN 202010138601 A CN202010138601 A CN 202010138601A CN 111307055 A CN111307055 A CN 111307055A
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- G01B11/00—Measuring arrangements characterised by the use of optical techniques
- G01B11/16—Measuring arrangements characterised by the use of optical techniques for measuring the deformation in a solid, e.g. optical strain gauge
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- G—PHYSICS
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- G01B—MEASURING LENGTH, THICKNESS OR SIMILAR LINEAR DIMENSIONS; MEASURING ANGLES; MEASURING AREAS; MEASURING IRREGULARITIES OF SURFACES OR CONTOURS
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- G01H—MEASUREMENT OF MECHANICAL VIBRATIONS OR ULTRASONIC, SONIC OR INFRASONIC WAVES
- G01H9/00—Measuring mechanical vibrations or ultrasonic, sonic or infrasonic waves by using radiation-sensitive means, e.g. optical means
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Abstract
The invention belongs to the field of pipeline safety and life cycle management, and particularly relates to a design method of a pipeline digital twin system. The modeling of the pipeline digital twin body adopts a global-local method, takes a real-time displacement acquisition value of a pipeline monitoring system as a displacement boundary condition, and takes a strain/temperature value of a detection optical fiber as check and correction data. And the evolution of the pipeline digital twin is promoted by applying a pipeline data mining analysis system. The pipeline digital twin system can display a pipeline high-risk area in real time, put forward internal detection requirements, suggest to supplement monitoring points, identify the falling position of a detection optical fiber, evaluate the safety margin of the pipeline, suggest a reinforcement method and predict the reinforcement effect.
Description
Technical Field
The invention belongs to the field of pipeline safety and life cycle management, and particularly relates to a design method of a pipeline digital twin system.
Background
The oil and gas pipeline is responsible for national energy supply, and the life cycle of the pipeline comprises the stages of pipe manufacturing, laying, joint welding, operation, geological disaster treatment, defect reinforcement, pipe replacement, scrapping and the like. The intrinsic safety of the pipeline in the life cycle is related to the pipeline material, the pipe manufacturing quality, the type, the quantity, the severity degree, the geographic environment, the burial depth, the operation age, the maintenance mode, the operation pressure and the like. In the whole life cycle of the pipeline, magnetic flux leakage internal detection and ultrasonic internal detection can be carried out regularly, and defect nondestructive external detection is carried out on the excavated buried pipeline, but the whole stress state and deformation displacement of the pipeline cannot be displayed in real time. The invention constructs a pipeline digital twin system based on a pipeline digital twin (developed based on a computer aided engineering software analysis system), a pipeline monitoring system, a pipeline internal/external nondestructive testing database, a pipeline design operation maintenance database and a pipeline data mining analysis system, wherein the pipeline digital twin and a geological disaster twin form a higher-level joint intelligent twin. The pipeline digital twin system has the functions of displaying the stress state and the deformation of the whole pipeline in real time, identifying a high-risk area of the pipeline, actively proposing internal detection requirements, suggesting and supplementing stress displacement/temperature monitoring points, identifying the falling position of a detection optical fiber, evaluating the safety margin of the pipeline, suggesting a defect reinforcing method, predicting the reinforcing effect and the like.
Disclosure of Invention
The invention aims to provide a design method of a pipeline digital twin system. The pipeline digital twin system comprises (1) a pipeline digital twin body (developed based on a computer aided engineering software analysis system), (2) a pipeline monitoring system, (3) a pipeline internal/external nondestructive testing database, (4) a pipeline design/operation maintenance database, and (5) a pipeline data mining and analyzing system, wherein the pipeline digital twin body (1) and the geological disaster twin body (6) form a higher-level joint intelligent twin body. The composition, function and relationship of the pipeline digital twin system are explained in detail below:
(1) the mechanical model of the pipeline digital twin body adopts a global-local modeling method, the global model is established based on a physical pipeline between two valve chambers, and the physical pipeline has the same material performance, geometric dimension and shape, space trend, buried depth, defect reinforcing position, soil landslide settlement/collapse burying control direction and the like; the local model considers the defects of the pipe body, the pipeline reinforcing structure, the contact stress distribution of the pipe body and the soil body, the constraint action of the soil body landslide/settlement/collapse treatment structure on the pipe body and the soil body and the like. The global model of the pipeline digital twin body can comprise a plurality of continuous or discontinuous pipelines between a plurality of valve chambers, and a physical pipeline between two valve chambers is taken as a unit segment.
Furthermore, the global model adopts the displacement value acquired by the pipeline monitoring system in real time as the displacement boundary condition, and adopts the continuous strain and temperature value (meter-level spatial resolution) acquired by the detection optical fiber in real time to check the simulation result and correct the global model.
And further, selecting a pipeline and a soil body with proper lengths according to the influence range of the pipeline defect stress field, and establishing a local model of the pipeline digital twin body. The local model needs to introduce the pipe-making residual stress, the mechanical boundary conditions at the two ends of the local model come from the simulation result of the global model, and the information of the types, positions and geometric dimensions of the defects come from the data information of the internal/external nondestructive testing of the pipeline.
Furthermore, predicting a defect initiation point according to the pipeline stress simulated by the pipeline digital twin body and the stress amplitude changing along with time; and the defect development speed is predicted by combining the defect information of the pipeline internal/external nondestructive testing database.
(2) The pipeline monitoring system consists of a series of sensors, a data acquisition module, a detection optical fiber (strain, temperature and vibration), an optical fiber signal transceiver, a wireless signal transceiver module, a solar power supply system (field), a power supply and lightning protection module and monitoring system software. The sensor comprises a strain gauge, a displacement meter and a level gauge. The strain, displacement and temperature (millimeter-scale spatial resolution) of the discrete monitoring points of the pipeline can be monitored in real time, and the strain, temperature and vibration acceleration values (meter-scale spatial resolution) of the pipeline along the line are continuous.
A high-displacement and high-stress area of the pipeline simulated by the digital twin provides a basis for the installation position of a newly added sensor of the monitoring system; the pipeline temperature and axial strain distribution result simulated by the digital twin provides a basis for identifying the falling position of the detection optical fiber; on the contrary, the pipeline monitoring system adds the acquisition information of the sensor, so as to further modify the prediction accuracy of the pipeline digital twin and improve the evolution degree of the pipeline digital twin.
(3) The pipeline inside/outside nondestructive detection database comprises data information of magnetic leakage defect inside detection, ultrasonic defect inside detection, stress inside detection and the like, and also comprises data information of X-ray nondestructive defect detection, ultrasonic nondestructive defect detection, magnetic powder inspection and the like after the buried pipeline is locally excavated. And keeping the continuous updating of the pipeline digital twin mechanical model according to the detected defect type, size, position and stress information.
(4) The pipeline design operation maintenance database comprises pipeline design information, operation pressure/temperature, maintenance information, soil landslide/settlement/collapse treatment information, third-party construction information and the like, and provides basic data for updating of a mechanical model, a constraint mode and an external load of a pipeline digital twin body.
(5) The pipeline data mining analysis system establishes an association rule set of pipeline defect initiation/development factors according to a pipeline internal/external nondestructive testing database, discrete stress/displacement/temperature monitoring information (millimeter-scale spatial resolution), continuous strain/temperature/vibration information (meter-scale spatial resolution), pipeline defect reinforcement information, soil landslide/settlement/collapse treatment information, third-party construction information and shared information of pipeline geological disaster twin bodies, forms a mode identification model of pipeline defect causes, and promotes the evolution of pipeline digital twin bodies.
Specifically, the sample information adopted by the pipeline data mining analysis system is divided into three types, namely early-stage data information, middle-stage data information and later-stage data information. The method comprises the following steps that firstly, sample data are used as training data of data mining, and a data mining prediction model is built according to the training data; taking the middle-stage sample data as correction data of the data mining model; and the later sample data is used as verification data of the data mining model. The three types of data are updated in sequence along with the increase of time, and the continuous evolution of the pipeline defect cause pattern recognition model is kept.
(6) The pipeline digital twin and the geological disaster twin form a higher-level joint intelligent twin. The geological disaster twin comprises a geographic information system, a stratum stress/displacement monitoring system, a camera security monitoring system and an unmanned aerial vehicle inspection system.
Specifically, the pipeline digital twin provides monitored pipeline stress/displacement/temperature/vibration information for the geological disaster twin, the geological disaster twin provides ground settlement/slippage/collapse monitoring information, ground stress monitoring information, soil moisture content, geographic information, camera monitoring information, unmanned aerial vehicle inspection information and the like along the pipeline for the pipeline digital twin, and the information of the two twins is kept to be interchanged. The joint intelligence of the two twin bodies is realized by sharing the pipeline stress field and displacement field information simulated by the pipeline digital twin body and the stratum stress field and displacement field information predicted by the geological disaster twin body.
According to the defect initiation and development prediction results of the pipeline digital twin system, the detection requirement in the pipeline is actively provided; and according to the defect safety margin evaluation result of the pipeline digital twin system, providing a defect reinforcing method and predicting the reinforcing effect.
Drawings
FIG. 1 is a structural diagram of a pipeline digital twinning system according to the present invention.
Detailed Description
In order to make the technical solution and advantages of the present invention clearer, the following description will explain embodiments of the present invention in detail with reference to the accompanying drawings.
As shown in fig. 1, a method for designing a pipeline digital twin system includes the following steps:
for the newly-built pipeline, according to the pipeline design information and the geographic information, a computer aided engineering software analysis system is adopted to simulate and obtain a high-risk section of the pipeline; and for the in-service pipeline, determining the high-risk section of the pipeline according to the defect type, the defect quantity and the defect severity of the in-service/out-service nondestructive testing database of the pipeline. The determination of high-risk sections can also be referred to the opinion of the pipeline owner and expert.
In a high-risk section of the pipeline, the pipeline between two valve chambers is selected as a physical pipeline unit section of a digital twin body, and a pipeline monitoring system is arranged and comprises a series of sensors, a data acquisition module, a detection optical fiber (temperature, vibration and strain), an optical fiber signal transceiver, a wireless signal transceiver module, a solar power supply system (field), a power supply and lightning protection module and monitoring system software. The sensor comprises a strain gauge, a displacement meter and a level gauge. The strain, displacement and temperature (millimeter-scale spatial resolution) of the discrete monitoring points of the pipeline can be monitored in real time, and the strain, temperature and vibration acceleration values (meter-scale spatial resolution) of the pipeline along the line are continuous. A digital twin may comprise a plurality of continuous or discontinuous segments of physical piping units. For a pipeline which is already put into operation, the corresponding digital twin is called a digital clone, and the two have the same inherent meanings.
A pipeline digital twin global pipeline-soil body geometric model is established according to the designed geometric dimension, space trend and buried depth of the pipeline, and the model is endowed with pipeline material mechanical properties, upper body mechanical properties, operation pressure, displacement boundary conditions of a valve chamber end and the like, so that a global model of the pipeline digital twin is established.
The global model adopts a real-time displacement value acquired by a pipeline monitoring system as a displacement boundary condition, and adopts continuous strain and temperature values (meter-level spatial resolution) acquired by a detection optical fiber in real time to check a stress simulation result and correct the global model.
The local model of the pipeline digital twin body needs to consider the pipe-making residual stress, the mechanical boundary conditions at two ends of the pipeline digital twin body come from the calculation result of the global model, and the information of the type, position and geometric dimension of the defect comes from the data of the internal/external nondestructive detection of the pipeline.
Predicting a possible defect initiation point according to the pipeline stress simulated by the pipeline digital twin body and the stress amplitude changing along with time; and the defect development speed is predicted by combining the defect information of the pipeline internal/external nondestructive testing database.
A high-displacement and high-stress area of the pipeline simulated by the digital twin provides a basis for the installation position of a newly added sensor of the monitoring system; the pipeline temperature and axial strain distribution result simulated by the digital twin provides a basis for identifying the falling position of the detection optical fiber; on the contrary, the pipeline monitoring system adds the acquisition information of the sensor, so as to further modify the prediction accuracy of the pipeline digital twin and improve the evolution degree of the pipeline digital twin.
Pipeline reinforcing structure information, soil landslide/settlement/collapse treatment information, third-party construction information and the like provided by a pipeline design/operation maintenance database provide basic data for updating a mechanical model, a constraint mode and an external load of a pipeline digital twin; and updating the local model of the pipeline based on the type, size and position information of the defects in the pipeline internal/external nondestructive testing database, and finishing one round of model evolution.
The pipeline data mining analysis system establishes an association rule set of pipeline defect initiation/development factors according to a pipeline internal/external nondestructive testing database, discrete stress/displacement/temperature monitoring information (millimeter-scale spatial resolution), continuous strain/temperature/vibration information (meter-scale spatial resolution), pipeline defect reinforcement information, soil landslide/settlement/collapse treatment information, second party construction information and shared information of pipeline geological disaster twin bodies, forms a mode identification model of pipeline defect causes, and promotes the evolution of pipeline digital twin bodies.
The sample information adopted by the pipeline data mining analysis system is divided into three types of early-stage data information, middle-stage data information and later-stage data information. The method comprises the following steps that firstly, sample data are used as training data of data mining, and a data mining prediction model is built according to the training data; taking the middle-stage sample data as correction data of the data mining model; and the later sample data is used as the prediction verification data of the data mining model. The three types of data are sequentially updated along with the increase of time, and the continuous evolution of the pipeline pattern recognition model is kept.
The pipeline digital twin and the geological disaster twin form a higher-level joint intelligent twin. The geological disaster twin comprises a geographic information system, a stratum stress/displacement monitoring system, a camera security monitoring system and an unmanned aerial vehicle inspection system. The pipeline digital twin body provides stress/displacement/temperature/vibration monitoring information of the pipeline for the geological disaster twin body, the geological disaster twin body provides ground settlement/slippage/collapse monitoring information, ground stress monitoring information, soil moisture content, geographic information, camera monitoring information, unmanned aerial vehicle inspection information and the like along the pipeline for the pipeline digital twin body, and the information of the two twin bodies is kept to be interchanged. The joint intelligence of the two twin bodies is realized by sharing the pipeline stress field and displacement field information simulated by the pipeline digital twin body and the stratum stress field and displacement field information predicted by the geological disaster twin body.
According to the defect initiation and development prediction results of the pipeline digital twin system, the detection requirement in the pipeline is actively provided; and according to the defect safety margin evaluation result of the pipeline digital twin system, providing a defect reinforcing method and predicting the reinforcing effect.
Claims (10)
1. A design method of a pipeline digital twin system is characterized in that the pipeline digital twin system is composed of a pipeline digital twin body (developed based on a computer aided engineering software analysis system), a pipeline monitoring system, a pipeline internal/external nondestructive testing database, a pipeline design/operation maintenance database and a pipeline data mining analysis system, wherein the pipeline digital twin body and a geological disaster twin body form a higher-level joint intelligent twin body.
2. The design method of the pipe digital twin system according to claim 1, characterized in that: a mechanical model of the pipeline digital twin body adopts a global-local modeling method, and the global model is established based on a physical pipeline between two valve chambers; the local model considers the local details of pipe body defects, pipeline reinforcing structures and the like, and the mechanical boundary conditions at two ends of the local model pipeline come from the simulation result of the global model.
3. The design method of the pipe digital twin system according to claim 1, characterized in that: the global model adopts a real-time displacement acquisition value of a pipeline monitoring system as a displacement boundary condition; and (5) verifying a stress simulation result by adopting the strain/temperature value acquired by the detection optical fiber in real time, and correcting the global model.
4. The design method of the pipe digital twin system according to claim 1, characterized in that: the local model needs to introduce the residual stress of the pipe making, and the type, position and geometric dimension of the defect come from the data of the internal/external nondestructive detection of the pipeline.
5. The design method of the pipe digital twin system according to claim 1, characterized in that: the high-displacement and high-stress area simulated by the pipeline digital twin body can provide a basis for the installation position of a newly added displacement and stress sensor of a pipeline monitoring system; the pipeline temperature and axial strain distribution result simulated by the digital twin provides a basis for identifying the falling position of the detection optical fiber; on the contrary, the pipeline stress/displacement monitoring system is additionally provided with the acquisition information of the sensor, so that the prediction accuracy of the pipeline digital twin is further modified, and the evolution degree of the pipeline digital twin is improved.
6. The design method of the pipe digital twin system according to claim 1, characterized in that: and the mechanical model of the pipeline digital twin body is kept synchronous with the updated data information of a pipeline design/operation maintenance database and a pipeline internal/external nondestructive testing database.
7. The design method of the pipe digital twin system according to claim 1, characterized in that: according to the sample data information of the data mining system, data in different time periods are used as training data, correction data and verification data according to time sequence, the three types of data are updated sequentially along with the increase of time, and the mode identification model of the pipeline defect cause is kept evolving continuously.
8. The design method of the pipe digital twin system according to claim 1, characterized in that: the pipeline digital twin and the geological disaster twin keep information exchange, and the joint intelligence of the two twins is realized.
9. The design method of the pipeline digital twin body according to claim 1 is suitable for not only the digital twin body of a newly built pipeline but also the digital clone body of an in-service pipeline.
10. The method for designing a pipeline digital twin according to claim 1, which is suitable for not only buried pipelines but also station pipelines.
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Cited By (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112413406A (en) * | 2020-12-04 | 2021-02-26 | 北京洪安科瑞科技有限责任公司 | Integrated pipeline block valve chamber and manufacturing method thereof |
| CN112728416A (en) * | 2020-12-18 | 2021-04-30 | 苏州热工研究院有限公司 | High-temperature high-pressure power pipeline state monitoring system |
| CN113837451A (en) * | 2021-09-06 | 2021-12-24 | 中控智网(北京)能源技术有限公司 | Digital twin body construction method, device, equipment and storage medium of oil and gas pipeline |
| CN113919106A (en) * | 2021-09-29 | 2022-01-11 | 大连理工大学 | Underground pipeline structure safety evaluation method based on augmented reality and digital twins |
| 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 |
| CN116129032A (en) * | 2022-10-02 | 2023-05-16 | 重庆蕴明科技股份有限公司 | Three-dimensional visual management system based on digital twin and construction method |
| CN116357899A (en) * | 2023-03-06 | 2023-06-30 | 上海市政工程设计研究总院（集团）有限公司 | Digital twin safety evaluation system and method for ultra-large caliber flexible pipeline |
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