CN116482227B - Pipeline corrosion monitoring method, device and system - Google Patents
Pipeline corrosion monitoring method, device and system Download PDFInfo
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Classifications
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N29/00—Investigating or analysing materials by the use of ultrasonic, sonic or infrasonic waves; Visualisation of the interior of objects by transmitting ultrasonic or sonic waves through the object
- G01N29/04—Analysing solids
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- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F17—STORING OR DISTRIBUTING GASES OR LIQUIDS
- F17D—PIPE-LINE SYSTEMS; PIPE-LINES
- F17D5/00—Protection or supervision of installations
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Abstract
The application relates to a method, a device and a system for monitoring pipeline corrosion. The method comprises the following steps: constructing a three-dimensional model of the pipeline through preset static data; after the pipeline enters an operation stage, measuring static data and environment data of the pipeline, and updating a three-dimensional model; when the pipeline enters an operation stage, acquiring real-time dynamic data of a plurality of areas in the pipeline through a plurality of sensors; preprocessing and storing the acquired dynamic data; generating a digital twin body of the pipeline according to the static data, the environmental data, the preprocessed dynamic data and the three-dimensional model; the extent of corrosion within the pipeline is monitored based on current dynamic data in the digital twin. The method comprehensively analyzes a plurality of types of data, comprehensively and accurately acquires the corrosion condition of the pipeline, realizes the real-time monitoring of the corrosion degree of the pipeline, does not need to consume a large amount of equipment and labor cost, and does not influence the operation of the pipeline.
Description
Technical Field
The application relates to the technical field of oil and gas pipelines, in particular to a method, a device and a system for monitoring pipeline corrosion.
Background
The oil gas pipeline transportation is a transportation mode for long-distance transportation of oil gas resources by adopting pipelines, and mainly connects oil and gas fields, refineries, ports, railways, highways and users to form a network, and has the advantages of low cost, high safety, small pollution, continuous and uninterrupted transportation and the like, so that the transportation mode becomes the main transportation mode of the current oil gas resources.
The pipeline corrosion problem needs to be considered in the pipeline transportation mode of oil gas, so that the pipeline corrosion condition needs to be monitored and maintained by manpower and material resources, and the pipeline corrosion monitoring and maintenance difficulty is brought due to the fact that the oil gas pipeline is relatively severe in buried environment. The corrosion problem of the pipeline directly affects the service life of the oil and gas pipeline, so that the corrosion condition of the oil and gas pipeline needs to be monitored to maintain the pipeline and prolong the service life of the pipeline. At present, for corrosion monitoring of oil and gas pipelines, the following modes exist:
nondestructive testing: the corrosion of the pipe is detected using ultrasonic, magnetic particle inspection, eddy current inspection, etc. techniques of this type can provide information about the thickness of the pipe wall and the extent of damage without damaging the pipe. However, the nondestructive test is suitable for corrosion monitoring of the surface of the pipeline, corrosion inside the pipeline is difficult to monitor, and the nondestructive test is usually required to be carried out during the period of non-working of the pipeline, so that the pipeline is required to be stopped, and the problems of production interruption, economic loss and the like are caused;
Electrochemical corrosion monitoring: and (3) by using an electrochemical technology, a corrosion prediction model is established to determine the corrosion rate and the corrosion type of the pipeline by measuring the potential and the current of the surface of the pipeline. This method can provide long-term corrosion monitoring data and can be used to detect localized corrosion conditions of the pipe. However, this approach requires a large amount of monitoring data to build the corrosion model, and therefore requires years to collect data and verify the model. In addition, this method may be affected by environmental factors such as soil and water quality around the pipe.
Inspection of the inside of a pipeline: and (5) using equipment such as an endoscope or a robot to enter the pipeline for inspection. Are commonly used to detect localized corrosion conditions of pipes, such as welds and bends in pipes. However, this approach is costly, takes a lot of time and effort to complete, and, in addition, it can become very difficult and expensive for pipelines in special areas such as deep water.
Therefore, a method capable of conveniently monitoring the pipeline in real time, comprehensively and accurately analyzing and predicting the corrosion degree in the pipeline is found, and the corrosion degree in the oil and gas pipeline is better monitored.
Disclosure of Invention
In view of the above, the application aims to provide a method, a device and a system for monitoring corrosion of a pipeline, and aims to monitor the corrosion degree in an oil and gas pipeline in real time and comprehensively and accurately analyze and evaluate the corrosion condition of the pipeline.
In order to achieve the above object, the embodiment of the present application provides the following technical solutions:
an embodiment of the present application provides a method for monitoring corrosion of a pipeline, including:
building a three-dimensional model of a pipeline through preset static data, wherein the pipeline is used for oil and gas transportation;
after the pipeline enters an operation stage, measuring static data and environment data of the pipeline, and updating the three-dimensional model; the static data comprises size data, material data, starting point data and end point data of the pipeline; the environmental data comprise soil physicochemical property data, pipeline burial depth data and peripheral stray current data around the pipeline;
when a pipeline enters an operation stage, acquiring real-time dynamic data of a plurality of areas in the pipeline through a plurality of sensors; the dynamic data comprise temperature data, pressure data, oil gas flow data and corrosion data of a plurality of areas in the pipeline; the sensor comprises a hanging piece sensor, a probe sensor and an ultrasonic sensor;
Preprocessing the acquired dynamic data and storing the preprocessed dynamic data;
generating a digital twin body of the pipeline according to the static data, the environment data, the preprocessed dynamic data and the three-dimensional model; the digital twin body and the pipeline have a dynamic data mapping relation;
and monitoring the corrosion degree in the pipeline according to the current dynamic data in the digital twin body.
Optionally, collecting real-time dynamic data of a plurality of areas in the pipeline by a plurality of sensors includes:
setting a collection period;
according to the collecting period, collecting the temperature, pressure and oil gas flow rate in the pipeline when the pipeline is not in operation and when the pipeline is in operation through sensors arranged in a plurality of areas in the pipeline; the sensor arranged in the pipeline is a hanging piece sensor or a probe sensor;
according to the acquisition period, acquiring corrosion data in the pipeline when the pipeline is not in operation and when the pipeline is in operation through sensors arranged in a plurality of areas outside the pipeline; the sensor arranged outside the pipeline is an ultrasonic sensor.
Optionally, preprocessing and storing the acquired dynamic data, including:
Preprocessing the dynamic data, wherein the preprocessing comprises data cleaning, format conversion and missing value processing;
carrying out data compression on the preprocessed dynamic data;
and storing the dynamic data after the data compression.
Optionally, generating a digital twin body of the pipeline comprises:
importing the static data into a GIS system to obtain the routing information of the pipeline;
importing the three-dimensional model into a simulation platform, and combining the routing information and the environmental data with the three-dimensional model to generate a digital twin body model;
synchronizing the dynamic data collected each time into the digital twin body model, and updating the current dynamic data in the digital twin body model;
and adjusting the digital twin body model to generate the digital twin body.
Optionally, adjusting the digital twin phantom includes:
predicting the dynamic data updated next time by using a machine learning algorithm according to the current dynamic data in the digital twin body model;
and after the current dynamic data in the digital twin body model is updated, adjusting the digital twin body model according to the difference between the predicted dynamic data and the current dynamic data until the difference is smaller than a set error threshold value.
Optionally, monitoring the corrosion level in the pipeline based on current dynamic data in the digital twin body, including:
acquiring current dynamic data in the digital twin;
calculating the current corrosion rate of the pipeline according to the current dynamic data;
monitoring the corrosion degree in the pipeline according to the corrosion rate;
setting an early warning threshold, and determining the position of the area and alarming to inform a manager when the corrosion degree in the pipeline exceeds the early warning threshold;
and predicting the residual life of the pipeline according to the current corrosion rate of the pipeline.
Optionally, preprocessing and storing the collected dynamic data, and further including:
storing the dynamic data to a cloud server;
and sharing the dynamic data to a plurality of local servers through the cloud server, so that distributed calculation is carried out on the dynamic data in the plurality of local servers, and corresponding corrosion rates are obtained.
Optionally, generating a digital twin body of the pipeline further comprises:
removing all sensor components in the digital twin body model, and reserving data of the sensor components;
And adjusting the digital twin body model according to the historical data of the stored dynamic data.
According to a second aspect of the embodiment of the present application, there is provided a pipe corrosion monitoring device for implementing the pipe corrosion monitoring method provided in the first aspect of the embodiment of the present application, the device including:
an initial model building module configured to build a three-dimensional model of a pipeline for oil and gas transportation using preset static data;
the data acquisition module is configured to measure static data and environment data of the pipeline after the pipeline enters an operation stage and update the three-dimensional model; the static data comprises size data, material data, starting point data and end point data of the pipeline; the environmental data comprise soil physicochemical property data, pipeline burial depth data and peripheral stray current data around the pipeline;
when a pipeline enters an operation stage, acquiring real-time dynamic data of a plurality of areas in the pipeline through a plurality of sensors; the dynamic data comprise temperature data, pressure data, oil gas flow data and corrosion data of a plurality of areas in the pipeline; the sensor comprises a hanging piece sensor, a probe sensor and an ultrasonic sensor;
The data preprocessing module is configured to preprocess the acquired dynamic data;
the storage module is configured to store the preprocessed dynamic data;
a monitoring module configured to generate a digital twin of the pipeline from the static data, the environmental data, the preprocessed dynamic data, and the three-dimensional model; the digital twin body and the pipeline have a dynamic data mapping relation;
and monitoring the corrosion degree in the pipeline according to the current dynamic data in the digital twin body.
According to a third aspect of the embodiment of the present application, there is provided a system for monitoring corrosion of a pipeline, for implementing the method for monitoring corrosion of a pipeline provided in the first aspect of the embodiment of the present application, the system including:
the model building unit is used for building a three-dimensional model of a pipeline, and the pipeline is used for oil and gas transportation;
the data acquisition unit is used for acquiring dynamic data of a plurality of areas in the pipeline through different types of sensors arranged inside and outside the pipeline; the sensor comprises a hanging piece sensor, a probe sensor and an ultrasonic sensor; the hanging piece sensor or the probe sensor is used for collecting the temperature, the pressure and the oil gas flow rate in the pipeline; the ultrasonic sensor is used for collecting corrosion data in the pipeline;
The data processing unit is used for receiving the dynamic data acquired by the data acquisition unit and preprocessing the dynamic data;
the storage unit is used for storing the dynamic data after the data processing unit performs preprocessing;
the simulation unit is used for generating a digital twin body of the pipeline according to the static data, the environment data, the preprocessed dynamic data and the three-dimensional model of the pipeline;
the synchronization unit is used for synchronizing the preprocessed dynamic data into the digital twin body;
and the calculating unit is used for calculating the current dynamic data in the digital twin body so as to monitor the corrosion degree in the pipeline.
By adopting the pipeline corrosion monitoring method provided by the application, a digital twin body model of the oil and gas pipeline is built, after the pipeline enters an operation stage, the real-time dynamic data of a plurality of areas in the pipeline are collected and synchronized to the digital twin body, so that the dynamic real-time data mapping of the digital twin body and the pipeline is realized, and the corrosion degree in the pipeline can be monitored by calculating and analyzing according to the current dynamic data in the digital twin body. According to the pipeline corrosion monitoring method provided by the application, the digital twin body with one-to-one data mapping with the entity pipeline is built, the real-time dynamic data in the pipelines of various types acquired by the sensors are synchronized into the digital twin body, the various types of data are comprehensively analyzed, the corrosion condition of the pipeline is comprehensively and accurately known, and the real-time monitoring of the corrosion degree of the pipeline is realized without consuming a large amount of equipment and labor cost and affecting the operation of the pipeline.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings that are needed in the description of the embodiments of the present application will be briefly described below, it being obvious that the drawings in the following description are only some embodiments of the present application, and that other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
FIG. 1 is a flow chart of a method for monitoring corrosion of a pipe according to an embodiment of the present application;
FIG. 2 is a schematic diagram of a pipe corrosion monitoring device according to an embodiment of the present application;
FIG. 3 is a schematic diagram of a pipe corrosion monitoring system according to an embodiment of the present application;
FIG. 4 is a schematic diagram of the architecture of a digital twin of a pipeline in an embodiment of the present application.
Detailed Description
The following description of the embodiments of the present application will be made clearly and fully with reference to the accompanying drawings, in which it is evident that the embodiments described are some, but not all embodiments of the application. All other embodiments, which can be made by those skilled in the art based on the embodiments of the application without making any inventive effort, are intended to be within the scope of the application.
It should be appreciated that reference throughout this specification to "one embodiment" or "an embodiment" means that a particular feature, structure or characteristic described in connection with the embodiment is included in at least one embodiment of the present application. Thus, the appearances of the phrases "in one embodiment" or "in an embodiment" in various places throughout this specification are not necessarily all referring to the same embodiment. Furthermore, the particular features, structures, or characteristics may be combined in any suitable manner in one or more embodiments.
In various embodiments of the present application, it should be understood that the sequence numbers of the following processes do not mean the order of execution, and the order of execution of the processes should be determined by the functions and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present application.
Reference will now be made in detail to exemplary embodiments, examples of which are illustrated in the accompanying drawings. When the following description refers to the accompanying drawings, the same numbers in different drawings refer to the same or similar elements, unless otherwise indicated. The implementations described in the following exemplary examples do not represent all implementations consistent with the application. Rather, they are merely examples of apparatus and methods consistent with aspects of the application as detailed in the accompanying claims.
It should be noted that, without conflict, the embodiments of the present application and features of the embodiments may be combined with each other.
Digital twinning is a technical means for creating a virtual entity of a physical entity in a digital mode, and simulating, verifying, predicting and controlling the whole life cycle process of the physical entity by means of historical data, real-time data, algorithm models and other data. In the embodiment, the digital twin body of the oil and gas pipeline entity is built so as to timely, accurately and comprehensively monitor the corrosion condition of the oil and gas pipeline, realize the automation of monitoring, reduce the cost of manual inspection and maintenance and improve the monitoring efficiency.
In the embodiment, the health state of the oil and gas pipeline is predicted through the digital twin body, so that early warning and quick response are realized, and the cost of pipeline maintenance and repair is reduced.
The application will be described in detail below with reference to the drawings in connection with embodiments.
FIG. 1 is a flow chart of a method for monitoring corrosion of a pipe according to an embodiment of the present application. As shown in fig. 1, the method comprises the steps of:
s11: and building a three-dimensional model of a pipeline through preset static data, wherein the pipeline is used for oil and gas transportation.
In this embodiment, the digital twin of the pipeline is built based on a three-dimensional model of the pipeline.
FIG. 4 is a schematic diagram of the architecture of a digital twin of a pipeline in an embodiment of the present application. As shown in fig. 4, the digital twin body of the pipeline comprises three parts: the pipeline part, the environment part and the fluid part are used for reducing the complexity and the operation amount of the system. Specifically, static data in a design stage is mainly used as preset data for building a three-dimensional model of a BIM (Building Information Mdeling, building information modeling) pipeline. In this embodiment, the building mode of the three-dimensional model of the pipeline is not limited, for example, BIM software can be used for building the model, and the initial three-dimensional model of the pipeline can be obtained by manually modeling on a three-dimensional modeling platform according to a CAD drawing.
The pipe portion of the digital twin includes dimensional data of the pipe, such as the pipe's dimensional size, wall thickness, pipe length, diameter, etc.; material data of the pipeline, including yield strength, fatigue strength and the like of the pipeline material; sensor data, including the type, number and mounting location of the sensors. In this embodiment, multiple types of sensors are disposed inside and outside the pipeline to collect different types of data. Specifically, a probe sensor or a hanging piece sensor is arranged in the pipeline and used for collecting data such as temperature, pressure, oil gas flow rate and the like in the pipeline; an ultrasonic sensor is arranged outside the pipeline and used for collecting ultrasonic signals reflected in the pipeline, and the ultrasonic signals are used as basic data for acquiring corrosion conditions of the pipeline.
In this embodiment, different types of sensors are placed at multiple locations within the pipe so that the monitoring range of the sensors covers all areas within the pipe.
The environmental portion of the digital twin includes soil physicochemical properties, pipe burial depth, stray current data around the pipe, and the like. The soil is composed of solid, liquid and gaseous three-phase substances, a solid framework composed of soil particles is filled with air, water and different salts, wherein the existence of the water and the soluble salts enables the soil to conduct ions, and the soil has the characteristics of electrolyte solution, so that electrochemical corrosion of metal in the soil occurs. Because the acid and alkaline degrees of the soil in different regions are different, the acidic medium and the alkaline medium contained in the soil are also greatly different, so that the influence of the soil in different regions on pipeline corrosion is also different. The different depths of pipeline burial can cause the temperature difference on pipeline surface, and the deeper pipeline burial in soil, its temperature is higher, and the rising of temperature also can lead to the corrosion rate of pipeline to increase. Around the oil and gas pipeline, there may be large electric facilities, such as railway, high-voltage direct current transmission line, etc., where the industrial and civil electricity is intentionally or unintentionally discharged or leaked to the ground, and the soil has stray current flowing into the pipeline, and electrolysis occurs, so that certain corrosion is caused to the pipeline.
The fluid part of the digital twin body mainly comprises data such as temperature, pressure, oil gas flow rate and the like of the fluid in the pipeline, and the data are determined in the design stage, so that the fluid data in the design stage can be used as dynamic data preset in the simulation of the digital twin body model.
S12: after the pipeline enters an operation stage, measuring static data and environment data of the pipeline, and updating the three-dimensional model; the static data comprises size data, material data, starting point data and end point data of the pipeline; the environmental data comprise soil physicochemical property data, pipeline burial depth data and peripheral stray current data around the pipeline;
s13: when a pipeline enters an operation stage, acquiring real-time dynamic data of a plurality of areas in the pipeline through a plurality of sensors; the dynamic data comprise temperature data, pressure data, oil gas flow data and corrosion data of a plurality of areas in the pipeline; the sensor comprises a hanging piece sensor, a probe sensor and an ultrasonic sensor.
In this embodiment, after the construction of the pipeline is completed, static data such as the actual size, the material, the start point and the end point information of the pipeline and the measured environmental data of the pipeline are measured, and the three-dimensional model is updated. After the pipeline enters the operation stage, real-time dynamic data of a plurality of areas in the pipeline are acquired through different types of sensors arranged in the pipeline. For example, real-time temperature, pressure and oil and gas flow data in the pipeline are collected by a probe sensor or a hanging piece sensor arranged in the pipeline. In this embodiment, corrosion data in the pipe is collected by an ultrasonic sensor disposed outside the pipe. Specifically, when an ultrasonic signal is collected, the ultrasonic signal is emitted into the pipeline through the ultrasonic probe, and the ultrasonic signal reflected in the pipeline is collected through the ultrasonic sensor and converted into an electric signal, so as to be used as basic data for analyzing the corrosion degree in the pipeline, namely, the corrosion data in the pipeline is included in the collected ultrasonic signal.
S131: setting an acquisition period.
In one embodiment, in order to realize real-time monitoring of dynamic data in a pipeline, an acquisition period is first set, and then various data in the pipeline are acquired according to the acquisition period. In practical application, the acquisition period can be set according to the operation condition of the pipeline or the type of the sensor. For example, the acquisition period set for the sensors that acquire temperature, pressure, and oil and gas flow rate may be a different acquisition period than the acquisition period for acquiring corrosion data within the pipeline.
S132: according to the collecting period, collecting the temperature, pressure and oil gas flow rate in the pipeline when the pipeline is not in operation and when the pipeline is in operation through sensors arranged in a plurality of areas in the pipeline; the sensor arranged in the pipeline is a hanging piece sensor or a probe sensor;
s133: according to the acquisition period, acquiring corrosion data in the pipeline when the pipeline is not in operation and when the pipeline is in operation through sensors arranged in a plurality of areas outside the pipeline; the sensor arranged outside the pipeline is an ultrasonic sensor.
In this embodiment, data acquisition is performed during non-operation and during operation of the pipeline, and dynamic data in the pipeline is monitored. When corrosion occurs in the pipeline, the non-working and working dynamic data collected by the sensor are different from the dynamic data (for example, the dynamic data preset in the design process of the pipeline) collected when the corrosion does not occur in the pipeline, so that whether the corrosion condition exists in the pipeline can be primarily judged according to the non-working and working dynamic data collected in the pipeline.
S14: preprocessing the acquired dynamic data and storing the preprocessed dynamic data.
In one embodiment, since the pipeline is affected by various external factors during the actual operation process, the dynamic data collected by the sensor contains a large amount of impurities, noise and useless information, and therefore, preprocessing is required before the dynamic data collected by a plurality of different types of sensors inside and outside the pipeline are used as basic data for monitoring corrosion.
S141: preprocessing the dynamic data, wherein the preprocessing comprises data cleaning, format conversion and missing value processing;
s143: and storing the dynamic data after the data compression.
In this embodiment, an edge computing technology is adopted, and preprocessing operations such as data cleaning, format conversion, missing value processing and the like are performed on dynamic data collected by a sensor in a local server, for example, noise and useless information are filtered, and collected ultrasonic signals are converted into digital signals and the like. And storing the dynamic data after the dynamic data preprocessing is completed.
In one embodiment, the processed dynamic data may be stored in a local server for convenient local reading.
S142: and carrying out data compression on the preprocessed dynamic data.
In one embodiment, to reduce the amount of data transferred, bandwidth resources and storage space are conserved, dynamic data is data compressed prior to storage.
S15: generating a digital twin body of the pipeline according to the static data, the environment data, the preprocessed dynamic data and the three-dimensional model; the digital twin has a dynamic data mapping relationship with the pipeline.
In this embodiment, static data, environmental data and preprocessed dynamic data acquired after the pipeline starts to operate are combined with an initial three-dimensional model to generate a digital twin body with dynamic data mapping corresponding to the pipeline one by one, and corrosion conditions of the pipeline are monitored through the digital twin body.
S151: importing the static data into a GIS system to obtain the routing information of the pipeline;
s152: importing the three-dimensional model into a simulation platform, and combining the routing information and the environmental data with the three-dimensional model to generate a digital twin body model;
s153: and synchronizing the dynamic data acquired each time into the digital twin body model, and updating the current dynamic data in the digital twin body model.
In one embodiment, static data of the pipeline, such as the start point and the end point of the pipeline, and information of the length, the diameter, the material and the like of the pipeline, are imported into the GIS system to obtain the routing information of the pipeline. After factors such as system maturity and expansibility are considered, a proper simulation platform (for example, units 3D, UE5 and the like) is selected for simulation. Specifically, a three-dimensional model of a pipeline is introduced into a simulation platform, measured static data and environment data are introduced, a digital twin body model is generated, real-time dynamic data acquired by a sensor and subjected to pretreatment are synchronized into the digital twin body model, and the dynamic data in the model are consistent with the current dynamic data in the pipeline.
S154: and adjusting the digital twin body model to generate the digital twin body.
S1541: predicting the dynamic data updated next time by using a machine learning algorithm according to the current dynamic data in the digital twin body model;
s1542: and after the current dynamic data in the digital twin body model is updated, adjusting the digital twin body model according to the difference between the predicted dynamic data and the current dynamic data until the difference is smaller than a set error threshold value.
In one embodiment, the digital twin model is required to be simulated and validated prior to being put into service, and adjusted to improve accuracy.
Specifically, the verification model is trained by using historical data of stored dynamic data and current dynamic data acquired recently through methods such as data mining, machine learning and the like. After the verification model training is completed, current dynamic data in the digital twin body model is input into the verification model, and the dynamic data which is synchronized into the digital twin body model next time, namely target dynamic data, is predicted and output through the verification model.
And after the dynamic data in the digital twin body model is updated, comparing the current updated dynamic data with the target dynamic data, and if a large error occurs between the current updated dynamic data and the target dynamic data, adjusting the digital twin body model according to the error and the actual situation. For example, a problematic sensor is replaced, new sensor data is added, and an adjustment mode such as correcting parameters of the digital twin model is added. And (3) repeatedly adjusting the digital twin body model until the errors of the digital twin body model and the digital twin body model are smaller than a set error threshold value, so that the digital twin body model achieves the accuracy standard, and a digital twin body capable of being put into formal operation is generated. The error threshold may be set according to the actual situation.
S16: and monitoring the corrosion degree in the pipeline according to the current dynamic data in the digital twin body.
In one embodiment, after the pipeline and the digital twin body of the simulation platform establish a dynamic data mapping relationship, the corrosion condition of the pipeline can be monitored in real time through the digital twin model. In this embodiment, the corrosion condition of the pipeline is mainly analyzed by dynamic data in the digital twin body, that is, the latest acquired dynamic data.
S161: acquiring current dynamic data in the digital twin;
s162: calculating the current corrosion rate of the pipeline according to the current dynamic data;
s163: and monitoring the corrosion degree in the pipeline according to the corrosion rate.
In one embodiment, a corrosion rate model is used to determine the corrosion of the pipe, and a quantitative representation of the current corrosion rate within the pipe is calculated from the current dynamic data in the digital twin. In this embodiment, the corrosion rate model may be a product corrosion rate model, a statistical corrosion rate model, an electrochemical corrosion model, or the like. It should be noted that, since all the areas in the whole pipeline are respectively located in the acquisition ranges of the plurality of sensors, when calculating the corrosion rate in the pipeline, dynamic data of each sensor coverage area needs to be calculated, and the current corrosion rate corresponding to the area needs to be obtained.
In one embodiment, machine learning algorithms, such as vector machines, neural networks, random forests, etc., may also be used to analyze the dynamic data for all areas within the pipeline to obtain a quantitative representation of the corrosion rate for all areas within the pipeline, i.e., a specific rate value.
In the above embodiment, the grade of the corrosion degree of all the areas in the pipeline can also be obtained according to the calculated corrosion rates of all the areas. For example, the corrosion level of a region within the pipe is determined to be "medium corrosion" or "mild corrosion" based on the corrosion rate of that region.
S164: and setting an early warning threshold, and determining the position of the area and alarming to inform a manager when the corrosion degree in the pipeline exceeds the early warning threshold.
In this embodiment, an early warning threshold is set according to the actual situation, and when the corrosion degree exceeds the early warning threshold, an alarm is given.
In one embodiment, the early warning threshold may be a corrosion rate. And acquiring an average value of the corrosion rate from the stored historical data of the corrosion rate, and adding a certain fluctuation range to the average value to determine the early warning threshold value. And when the corrosion rate of a certain area in the pipeline exceeds the early warning threshold value, positioning the area and generating alarm information.
In one embodiment, the early warning threshold may be an increase in the corrosion rate. And obtaining a mean value of corrosion rate increment from stored historical data of the corrosion rate, wherein the corrosion rate increment is the increment of the corrosion rate in a period of time compared with the corrosion rate before the period of time. And determining the corrosion rate increment as an early warning threshold value, and when the corrosion rate increment of a certain area in the pipeline exceeds the early warning threshold value, positioning the area and generating alarm information.
In one embodiment, the corrosion threshold may be a level of corrosion, such as setting a "light corrosion" level to an early warning threshold. And when the corrosion degree level of the area in the pipeline exceeds the early warning threshold value, positioning the area and generating alarm information. For example, if the corrosion degree of the area 1 is "moderate corrosion", and the early warning threshold "light corrosion" is exceeded, the area 1 is located and alarm information is generated.
In the above embodiment, the alarm information may notify the manager by means of a short message, a mail, or a terminal display information.
S165: and predicting the residual life of the pipeline according to the current corrosion rate of the pipeline.
In one embodiment, a machine learning algorithm is used to predict the remaining life of the pipeline based on the current corrosion rate and the current corrosion condition of the pipeline when the corrosion rate in the pipeline is obtained based on the current dynamic data, thereby facilitating maintenance and repair by personnel.
Optionally, in step S14, the collected dynamic data is preprocessed and stored, and the method further includes the following sub-steps:
s144: storing the dynamic data to a cloud server;
s145: and sharing the dynamic data to a plurality of local servers through the cloud server, so that distributed calculation is carried out on the dynamic data in the plurality of local servers, and corresponding corrosion rates are obtained.
In one embodiment, the preprocessed data is uploaded to a cloud server for storage. The cloud server shares the stored dynamic data to a plurality of local servers, and performs distributed computation in the plurality of local servers, so that a mode of performing centralized computation by using one server under normal conditions is converted into a distributed computation mode of splitting the dynamic data into the plurality of local servers to be computed separately, and each local server only needs to compute the dynamic data of a part of split areas. The calculation speed can be improved by adopting a distributed calculation mode, and the requirement of monitoring the corrosion condition of the pipeline in real time can be met under the condition of large calculation data volume. And after the calculation of all the local servers is finished, summarizing the calculation results of the pipeline corrosion rates of all the areas to obtain the corrosion rates of all the areas in the pipeline.
S156: removing all sensor components in the digital twin body model, and reserving data of the sensor components;
s157: and adjusting the digital twin body model according to the historical data of the stored dynamic data.
In one embodiment, after the three-dimensional model is imported into the simulation platform, in order to reduce the memory occupation of the system, the model is subjected to light weight processing, auxiliary components (such as various sensors arranged inside and outside a pipeline) which are irrelevant to pipeline operation in the three-dimensional model are omitted, and only the data of the auxiliary components are reserved.
Based on the same inventive concept, an embodiment of the application provides a pipeline corrosion monitoring device. Referring to FIG. 2, FIG. 2 is a schematic diagram of a pipe corrosion monitoring apparatus 200 according to an embodiment of the present application. As shown in fig. 2, the apparatus includes:
an initial model building module 201 configured to build a three-dimensional model of a pipeline for oil and gas transportation by preset static data;
a data acquisition module 202 configured to measure static data and environmental data of the pipeline and update the three-dimensional model when the pipeline enters an operational phase; the static data comprises size data, material data, starting point data and end point data of the pipeline; the environmental data comprise soil physicochemical property data, pipeline burial depth data and peripheral stray current data around the pipeline;
When a pipeline enters an operation stage, acquiring real-time dynamic data of a plurality of areas in the pipeline through a plurality of sensors; the dynamic data comprise temperature data, pressure data, oil gas flow data and corrosion data of a plurality of areas in the pipeline; the sensor comprises a hanging piece sensor, a probe sensor and an ultrasonic sensor;
a data preprocessing module 203 configured to preprocess the acquired dynamic data;
a storage module 204 configured to store the preprocessed dynamic data;
a monitoring module 205 configured to generate a digital twin of the pipeline from the static data, the environmental data, the preprocessed dynamic data, and the three-dimensional model; the digital twin body and the pipeline have a dynamic data mapping relation;
and monitoring the corrosion degree in the pipeline according to the current dynamic data in the digital twin body.
Optionally, the data acquisition module 202 is further configured to perform the steps of:
according to the acquisition period, acquiring the temperature, pressure and oil gas flow rate in the pipeline when the pipeline is not in operation and when the pipeline is in operation through sensors arranged in a plurality of areas in the pipeline; the sensor arranged in the pipeline is a hanging piece sensor or a probe sensor;
According to the acquisition period, acquiring corrosion data in the pipeline when the pipeline is not in operation and when the pipeline is in operation through sensors arranged in a plurality of areas outside the pipeline; the sensor arranged outside the pipeline is an ultrasonic sensor.
Optionally, the data preprocessing module 203 is configured to preprocess the dynamic data, where preprocessing includes data cleansing, format conversion, and missing value processing;
and carrying out data compression on the preprocessed dynamic data.
Optionally, the storage module 204 is configured to store the dynamic data after the data compression.
Optionally, the monitoring module 205 further includes;
the simulation module is configured to import the static data into a GIS system and acquire the routing information of the pipeline; importing the three-dimensional model into a simulation platform, and combining the routing information and the environmental data with the three-dimensional model to generate a digital twin body model; synchronizing the dynamic data collected each time into the digital twin body model, and updating the current dynamic data in the digital twin body model;
an adjustment module configured to predict next updated dynamic data using a machine learning algorithm based on current dynamic data in the digital twin model; and after the current dynamic data in the digital twin body model is updated, adjusting the digital twin body model according to the difference between the predicted dynamic data and the current dynamic data until the difference is smaller than a set error threshold value.
Optionally, the monitoring module 205 further includes:
a corrosion monitoring sub-module configured to obtain current dynamic data in the digital twin; calculating the current corrosion rate of the pipeline according to the current dynamic data; monitoring the corrosion degree in the pipeline according to the corrosion rate;
the early warning sub-module is configured to set an early warning threshold, and when the corrosion degree in the pipeline exceeds the early warning threshold, the position of the area is determined and the manager is warned and notified;
a prediction sub-module configured to predict a remaining life of the pipe based on a current corrosion rate of the pipe.
Optionally, the storage module 204 is further configured to store the dynamic data to a cloud server;
and sharing the dynamic data to a plurality of local servers through the cloud server, so that distributed calculation is carried out on the dynamic data in the plurality of local servers, and corresponding corrosion rates are obtained.
Optionally, the simulation module is further configured to remove all sensor components in the digital twin body model, and retain data of the sensor components.
The adjustment module is further configured to adjust the digital twin model based on historical data of the stored dynamic data.
Optionally, the pipe corrosion monitoring device 200 further includes:
the control module is configured to control the ultrasonic probe to emit signals into the pipeline according to the set signal emission period;
and controlling an ultrasonic sensor to collect ultrasonic signals reflected in the pipeline according to the collecting period.
Based on the same inventive concept, an embodiment of the present application provides a pipe corrosion monitoring system. Referring to FIG. 3, FIG. 3 is a schematic diagram of a pipe corrosion monitoring system 300 according to an embodiment of the present application. As shown in fig. 3, the system includes:
a model building unit 301 for building a three-dimensional model of a pipeline for oil and gas transportation;
the data acquisition unit 302 is configured to acquire dynamic data of a plurality of areas in the pipeline through different types of sensors disposed inside and outside the pipeline; the sensor comprises a hanging piece sensor, a probe sensor and an ultrasonic sensor; the hanging piece sensor or the probe sensor is used for collecting the temperature, the pressure and the oil gas flow rate in the pipeline; the ultrasonic sensor is used for collecting corrosion data in the pipeline;
the data processing unit 303 is configured to receive the dynamic data collected by the data collecting unit, and perform preprocessing on the dynamic data;
A storage unit 304, configured to store the dynamic data after the preprocessing by the data processing unit;
a simulation unit 305, configured to generate a digital twin body of the pipeline according to the static data, the environmental data, the preprocessed dynamic data and the three-dimensional model of the pipeline;
a synchronizing unit 306, configured to synchronize the preprocessed dynamic data into the digital twin;
a calculation unit 307 for calculating current dynamic data in the digital twin body, thereby monitoring the degree of corrosion in the pipeline.
In the embodiment, the digital twin body can also be used for full life cycle management of the oil and gas pipeline, and the intelligent, comprehensive and fine level of pipeline management is improved from the design and construction of the pipeline to the comprehensive monitoring and management of the operation, maintenance and retirement of the pipeline.
The specific manner in which the various modules perform the operations in the apparatus of the above embodiments have been described in detail in connection with the embodiments of the method, and will not be described in detail herein.
The foregoing description of the preferred embodiments of the application is not intended to be limiting, but rather is intended to cover all modifications, equivalents, alternatives, and improvements that fall within the spirit and scope of the application.
For the purposes of simplicity of explanation, the methodologies are shown as a series of acts, but one of ordinary skill in the art will recognize that the present application is not limited by the order of acts described, as some acts may, in accordance with the present application, occur in other orders and concurrently. Further, those skilled in the art will recognize that the embodiments described in the specification are all of the preferred embodiments, and that the acts and components referred to are not necessarily required by the present application.
It will be apparent to those skilled in the art that embodiments of the present application may be provided as a method, apparatus, or computer program product. Accordingly, embodiments of the present application may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, embodiments of the application may take the form of a computer program product on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) having computer-usable program code embodied therein.
Embodiments of the present application are described with reference to flowchart illustrations and/or block diagrams of methods, terminal devices (systems), and computer program products according to embodiments of the application. It will be understood that each flow and/or block of the flowchart illustrations and/or block diagrams, and combinations of flows and/or blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing terminal device to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing terminal device, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
While preferred embodiments of the present application have been described, additional variations and modifications in those embodiments may occur to those skilled in the art once they learn of the basic inventive concepts. It is therefore intended that the following claims be interpreted as including the preferred embodiment and all such alterations and modifications as fall within the scope of the embodiments of the application.
Finally, it is further noted that relational terms such as first and second, and the like are used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Moreover, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or terminal that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or terminal. Without further limitation, an element defined by the phrase "comprising one … …" does not exclude the presence of other like elements in a process, method, article or terminal device comprising the element.
The method, the device and the system for monitoring the pipeline corrosion provided by the application are described in detail, and specific examples are applied to the description of the principle and the implementation mode of the application, and the description of the examples is only used for helping to understand the method and the core idea of the application; meanwhile, as those skilled in the art will have variations in the specific embodiments and application scope in accordance with the ideas of the present application, the present description should not be construed as limiting the present application in view of the above.
Claims (9)
1. A method of monitoring corrosion of a pipe, comprising:
building a three-dimensional model of a pipeline through preset static data, wherein the pipeline is used for oil and gas transportation;
after the pipeline enters an operation stage, measuring static data and environment data of the pipeline, and updating the three-dimensional model; the static data comprises size data, material data, starting point data and end point data of the pipeline; the environmental data comprise soil physicochemical property data, pipeline burial depth data and peripheral stray current data around the pipeline;
when the pipeline enters an operation stage, acquiring real-time dynamic data of a plurality of areas in the pipeline through a plurality of sensors of different types, wherein the acquisition range of the plurality of sensors of different types covers all the areas in the pipeline; the dynamic data comprise temperature data, pressure data, oil gas flow data and corrosion data of a plurality of areas in the pipeline; the sensor comprises a hanging piece sensor, a probe sensor and an ultrasonic sensor;
preprocessing the acquired dynamic data and storing the preprocessed dynamic data;
generating a digital twin body of the pipeline according to the static data, the environment data, the preprocessed dynamic data and the three-dimensional model; the digital twin body has a dynamic data mapping relation with the pipeline, predicts dynamic data updated next time according to the current dynamic data, and the predicted dynamic data updated next time is used for comparing with the dynamic data updated next time actually;
Monitoring the corrosion level in the pipeline according to the current dynamic data in the digital twin body, comprising: acquiring current dynamic data in the digital twin;
calculating the current corrosion rate of the pipeline according to the current dynamic data;
monitoring the corrosion degree in the pipeline according to the corrosion rate;
setting an early warning threshold, and determining the position of the area and alarming to inform a manager when the corrosion degree in the pipeline exceeds the early warning threshold;
and predicting the residual life of the pipeline according to the current corrosion rate of the pipeline.
2. The method of claim 1, wherein collecting real-time dynamic data of a plurality of areas within the pipe with a plurality of different types of sensors comprises:
setting a collection period;
according to the collecting period, collecting the temperature, pressure and oil gas flow rate in the pipeline when the pipeline is not in operation and when the pipeline is in operation through sensors arranged in a plurality of areas in the pipeline; the sensors arranged in a plurality of areas in the pipeline are hanging sheet sensors or probe sensors;
according to the acquisition period, acquiring corrosion data in the pipeline when the pipeline is not in operation and when the pipeline is in operation through sensors arranged in a plurality of areas outside the pipeline; the sensors arranged in a plurality of areas outside the pipeline are ultrasonic sensors.
3. The method of claim 1, wherein the preprocessing and storing of the collected dynamic data includes:
preprocessing the dynamic data, wherein the preprocessing comprises data cleaning, format conversion and missing value processing;
carrying out data compression on the preprocessed dynamic data;
and storing the dynamic data after data compression.
4. A method of monitoring corrosion of a pipe according to claim 3, wherein generating a digital twin of the pipe comprises:
importing the static data into a GIS system to obtain the routing information of the pipeline;
importing the three-dimensional model into a simulation platform, and combining the routing information and the environmental data with the three-dimensional model to generate a digital twin body model;
synchronizing the dynamic data collected each time into the digital twin body model, and updating the current dynamic data in the digital twin body model;
and adjusting the digital twin body model to generate the digital twin body.
5. The method of claim 4, wherein adjusting the digital twin body model comprises:
Predicting the dynamic data updated next time by using a machine learning algorithm according to the current dynamic data in the digital twin body model;
and after the current dynamic data in the digital twin body model is updated, adjusting the digital twin body model according to the predicted difference between the dynamic data and the current dynamic data until the difference is smaller than a set error threshold value.
6. The method of claim 1, wherein the collected dynamic data is preprocessed and stored, further comprising:
storing the dynamic data to a cloud server;
and sharing the dynamic data to a plurality of local servers through the cloud server, so that distributed calculation is carried out on the dynamic data in the plurality of local servers, and corresponding corrosion rates are obtained.
7. The method of monitoring corrosion of a pipe of claim 4, wherein generating a digital twin body of the pipe further comprises:
removing all sensor components in the digital twin body model, and reserving data of the sensor components;
and adjusting the digital twin body model according to the historical data of the stored dynamic data.
8. A pipe corrosion monitoring apparatus for implementing the pipe corrosion monitoring method of any one of claims 1 to 7, comprising:
an initial model building module configured to build a three-dimensional model of a pipeline for oil and gas transportation using preset static data;
the data acquisition module is configured to measure static data and environment data of the pipeline after the pipeline enters an operation stage and update the three-dimensional model; the static data comprises size data, material data, starting point data and end point data of the pipeline; the environmental data comprise soil physicochemical property data, pipeline burial depth data and peripheral stray current data around the pipeline;
when the pipeline enters an operation stage, acquiring real-time dynamic data of a plurality of areas in the pipeline through a plurality of sensors of different types, wherein the acquisition range of the plurality of sensors of different types covers all the areas in the pipeline; the dynamic data comprise temperature data, pressure data, oil gas flow data and corrosion data of a plurality of areas in the pipeline; the sensor comprises a hanging piece sensor, a probe sensor and an ultrasonic sensor;
The data preprocessing module is configured to preprocess the acquired dynamic data;
the storage module is configured to store the preprocessed dynamic data;
a monitoring module configured to generate a digital twin of the pipeline from the static data, the environmental data, the preprocessed dynamic data, and the three-dimensional model; the digital twin body has a dynamic data mapping relation with the pipeline, predicts dynamic data updated next time according to the current dynamic data, and the predicted dynamic data updated next time is used for comparing with the dynamic data updated next time actually;
monitoring the corrosion level in the pipeline according to the current dynamic data in the digital twin body, comprising: acquiring current dynamic data in the digital twin;
calculating the current corrosion rate of the pipeline according to the current dynamic data;
monitoring the corrosion degree in the pipeline according to the corrosion rate;
setting an early warning threshold, and determining the position of the area and alarming to inform a manager when the corrosion degree in the pipeline exceeds the early warning threshold;
And predicting the residual life of the pipeline according to the current corrosion rate of the pipeline.
9. A pipe corrosion monitoring system for implementing the pipe corrosion monitoring method of any one of claims 1-7, comprising:
the model building unit is used for building a three-dimensional model of a pipeline, and the pipeline is used for oil and gas transportation;
the data acquisition unit is used for acquiring dynamic data of a plurality of areas in the pipeline through different types of sensors arranged inside and outside the pipeline; the sensor comprises a hanging piece sensor, a probe sensor and an ultrasonic sensor; the hanging piece sensor or the probe sensor is used for collecting the temperature, the pressure and the oil gas flow rate in the pipeline; the ultrasonic sensor is used for collecting corrosion data in the pipeline;
the data processing unit is used for receiving the dynamic data acquired by the data acquisition unit and preprocessing the dynamic data;
the storage unit is used for storing the dynamic data after the data processing unit performs preprocessing;
the simulation unit is used for generating a digital twin body of the pipeline according to the static data, the environment data, the preprocessed dynamic data and the three-dimensional model of the pipeline;
The synchronization unit is used for synchronizing the preprocessed dynamic data into the digital twin body;
and the calculating unit is used for calculating the current dynamic data in the digital twin body so as to monitor the corrosion degree in the pipeline.
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