CN114294570A - Oil-gas pipeline stress monitoring and early warning method and system, storage medium and electronic device - Google Patents
Oil-gas pipeline stress monitoring and early warning method and system, storage medium and electronic device Download PDFInfo
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Abstract
The application discloses an oil and gas pipeline stress monitoring and early warning method, a system, a storage medium and an electronic device. The method comprises the following steps: remotely acquiring a plurality of groups of monitoring data monitored by a data acquisition module and corresponding to a plurality of monitoring points; determining an early warning model corresponding to each monitoring point according to the operation parameters of the pipeline and a group of monitoring data of each monitoring point; processing the monitoring data of each monitoring point according to the stress state calculation model to obtain the stress states of the monitoring points, and determining the early warning level corresponding to the stress state of the monitoring point through the early warning level table corresponding to each monitoring point; and displaying the stress state, the monitoring data and the early warning level of the monitoring points, and giving an alarm when the early warning level corresponding to the stress state exceeds a preset level. By the method and the device, the problems that the stress of the pipeline cannot be effectively monitored in real time, the stress state of the pipeline cannot be accurately judged, and early warning cannot be timely performed on abnormal stress states of the pipeline in the related technology are solved.
Description
Technical Field
The application relates to the field of monitoring and early warning, in particular to an oil and gas pipeline stress monitoring and early warning method, system, storage medium and electronic device.
Background
With the continuous expansion of the construction scale of oil and gas pipelines, when the oil and gas pipelines are constructed, a plurality of oil and gas pipelines inevitably pass through areas with large climate difference, frequent geological activity and complex geological environment. In the part of areas, the types of geological disasters along pipelines are various, wherein the geological disasters such as landslides and debris flows and the hidden dangers thereof are wide in distribution and large in damage, and the operation state, the production and the construction of the pipelines are greatly influenced. Therefore, accurate monitoring of the stress state of the pipeline has become a key task for preventing pipeline accidents and guaranteeing safe operation of the pipeline.
Some pipeline stress monitoring devices and early warning methods appear in the related art, but the pipeline stress monitoring devices in the related art are poor in universality, high in energy consumption and greatly influenced by regions and environments, so that the monitoring precision is low, the stress states of multiple pipeline sections of a pipeline are difficult to obtain in time, a risk level of the pipeline cannot be accurately judged by an early warning model, and then when the stress state of the pipeline is abnormal, maintenance measures are difficult to take in time and effectively.
The method aims at solving the problems that the stress of the pipeline cannot be effectively monitored in real time, the stress state of the pipeline cannot be accurately judged, and early warning cannot be timely performed on abnormal stress state of the pipeline in the related technology. No effective solution has been proposed so far.
Disclosure of Invention
The application provides an oil and gas pipeline stress monitoring and early warning method, a system, a storage medium and an electronic device, which are used for solving the problems that the pipeline stress cannot be effectively monitored in real time, the stress state of a pipeline cannot be accurately judged, and early warning cannot be timely performed on abnormal pipeline stress states in the related technology.
According to one aspect of the application, an oil and gas pipeline stress monitoring and early warning method is provided. The method comprises the following steps: the method comprises the steps of remotely acquiring multiple groups of monitoring data which are monitored by a data acquisition module and correspond to multiple monitoring points, wherein the monitoring data comprise strain data and temperature data; determining an early warning model corresponding to each monitoring point according to the operation parameters of the pipeline and a group of monitoring data of each monitoring point, wherein the early warning model comprises a stress state calculation model and an early warning level table, and the early warning level table is used for representing the corresponding relation between different early warning levels and different stress states; processing the monitoring data of each monitoring point according to the stress state calculation model to obtain the stress states of the monitoring points, and determining the early warning level corresponding to the stress state of the monitoring point through the early warning level table corresponding to each monitoring point; and displaying the stress state, the monitoring data and the early warning level of the monitoring points, and giving an alarm when the early warning level corresponding to the stress state exceeds a preset level.
Optionally, the stress state calculation model is:
wherein beta is the stress state and V sigma is the axial stress of the pipelineMonitoring values, wherein delta sigma is more than or equal to 0 for pipeline stretching, delta sigma is less than 0 for pipeline compression, mu is pipe Poisson's ratio, and P is0In order to take the operation pressure during the monitoring measure, d is the inner diameter of the pipeline, T is the wall thickness of the pipeline, alpha is the linear expansion coefficient of the pipe, E is the elastic modulus of the pipe, and T is1For the wall temperature, T, at which monitoring measures are taken0Is the initial temperature of the tube wall, P1For operating pressure of the pipe, σsIs the minimum yield strength of the pipe.
Optionally, the stress state and the monitoring data of the multiple monitoring points are displayed: determining a target monitoring point in the multiple monitoring points, and determining the number of a target sensor in the target monitoring point; and acquiring target characteristic data and stress states corresponding to the target characteristic data from the monitoring data of the multiple monitoring points according to the serial numbers of the target sensors to obtain target data, and displaying the target data through a preset type chart, wherein the stress states are related to the serial numbers of the corresponding sensors and the corresponding monitoring data.
Optionally, the method further includes: the method comprises the following steps of displaying historical stress states and historical monitoring data of a plurality of monitoring points, wherein the steps comprise: determining a query condition, wherein the query condition at least comprises one of the following conditions: the number of the measuring point, the number of the sensor, the starting time, the ending time and the early warning level corresponding to the stress state; and screening the historical stress states and the historical monitoring data of the multiple monitoring points of the pipeline according to the query conditions to obtain screened data, and displaying the screened data through a preset type chart.
Optionally, the alarming when the early warning level corresponding to the stress state exceeds a preset level includes: an alarm device arranged on the monitoring platform sends out an alarm signal; and/or sending an alarm notification message to the terminal equipment associated with the monitoring platform.
According to one aspect of the application, an oil and gas pipeline stress monitoring and early warning system is provided. The system comprises: the system comprises a plurality of groups of sensors, a monitoring unit and a monitoring unit, wherein the plurality of groups of sensors are respectively arranged at a plurality of monitoring points of a pipeline and are used for acquiring pipeline characteristic signals corresponding to the monitoring points, and the pipeline characteristic signals comprise stress characteristic signals and temperature characteristic signals; the system comprises at least one data acquisition module, a cloud server and a monitoring server, wherein the data acquisition modules are respectively arranged in monitoring boxes of monitoring piles which are matched with each other, each data acquisition module is connected with a sensor corresponding to at least one monitoring point, receives pipeline characteristic signals acquired by the sensors of the at least one monitoring point, processes the received pipeline characteristic signals into monitoring data, and sends the monitoring data to the cloud server; the cloud server is communicated with the at least one data acquisition module and is used for transmitting a control instruction to the data acquisition module and receiving monitoring data; the monitoring platform is in wireless communication connection with the cloud server and used for acquiring monitoring data, determining the stress state of each monitoring point of the pipeline through the monitoring data and a stress state calculation model in the early warning model, determining the early warning level corresponding to the stress state through an early warning level table in the early warning model, and giving an alarm when the early warning level corresponding to the stress state exceeds a preset level, wherein the early warning level table is used for representing the corresponding relation between different early warning levels and different stress states.
Optionally, each sensor of the plurality of sets of sensors comprises: the strain sensors are arranged on the axial outer wall of the pipeline where the monitoring points are located and used for acquiring strain data of the monitoring points; wherein, be provided with temperature sensor on every strain sensor for acquire the temperature data of monitoring point.
Optionally, the oil and gas pipeline stress monitoring and early warning system further comprises: monitoring pile, including the support column, be provided with monitoring case, renewable energy power generation facility and orientation module on the support column, wherein, orientation module is used for confirming the positional information who monitors the pile, and the storage has data acquisition module and wireless communication module in the monitoring case, and renewable energy power generation facility includes the battery for to data acquisition module power supply, wireless communication module and data acquisition module are connected, in order to support the communication between data acquisition module and the cloud ware.
According to another aspect of the embodiment of the invention, a nonvolatile storage medium is further provided, and the nonvolatile storage medium comprises a stored program, wherein the program controls the equipment where the nonvolatile storage medium is located to execute the method for monitoring and warning the stress of the oil and gas pipeline during running.
According to another aspect of the embodiments of the present invention, there is also provided an electronic device, including a processor and a memory; the storage is stored with computer readable instructions, and the processor is used for operating the computer readable instructions, wherein the computer readable instructions execute a stress monitoring and early warning method for the oil and gas pipeline when running.
Through the application, the following steps are adopted: the method comprises the steps of remotely acquiring multiple groups of monitoring data which are monitored by a data acquisition module and correspond to multiple monitoring points, wherein the monitoring data comprise strain data and temperature data; determining an early warning model corresponding to each monitoring point according to the operation parameters of the pipeline and a group of monitoring data of each monitoring point, wherein the early warning model comprises a stress state calculation model and an early warning level table, and the early warning level table is used for representing the corresponding relation between different early warning levels and different stress states; processing the monitoring data of each monitoring point according to the stress state calculation model to obtain the stress states of the monitoring points, and determining the early warning level corresponding to the stress state of the monitoring point through the early warning level table corresponding to each monitoring point; and displaying the stress state, the monitoring data and the early warning level of the monitoring points, and giving an alarm when the early warning level corresponding to the stress state exceeds a preset level. The problem of can't monitor pipeline stress effectively in real time among the correlation technique, can't accurately judge the stress state of pipeline, and can't in time carry out the early warning to pipeline stress state anomaly is solved. Data are collected through a plurality of groups of sensors arranged at each monitoring point of the pipeline, and the stress state of the pipeline is judged and early warned by combining an early warning model, so that the monitoring, early warning and evaluation capabilities of the stress state of the oil-gas pipeline are effectively improved, and the safe operation effect of the oil-gas pipeline is guaranteed.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this application, illustrate embodiments of the application and, together with the description, serve to explain the application and are not intended to limit the application. In the drawings:
FIG. 1 is a schematic diagram of an oil and gas pipeline stress monitoring and early warning system provided according to an embodiment of the application;
FIG. 2 is a schematic diagram of an alternative data acquisition module provided in accordance with an embodiment of the present application;
FIG. 3 is a flow chart of an alternative data collection and data query method provided in accordance with an embodiment of the present application.
FIG. 4 is a schematic structural diagram of an alternative hydrocarbon pipeline stress monitoring and warning system provided in an embodiment of the present application;
FIG. 5 is a flow chart of a method for monitoring and warning the stress of an oil and gas pipeline according to an embodiment of the application;
Detailed Description
It should be noted that the embodiments and features of the embodiments in the present application may be combined with each other without conflict. The present application will be described in detail below with reference to the embodiments with reference to the attached drawings.
In order to make the technical solutions better understood by those skilled in the art, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are only partial embodiments of the present application, but not all embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present application.
It should be noted that the terms "first," "second," and the like in the description and claims of this application and in the drawings described above are used for distinguishing between similar elements and not necessarily for describing a particular sequential or chronological order. It should be understood that the data so used may be interchanged under appropriate circumstances such that embodiments of the application described herein may be used. Furthermore, the terms "comprises," "comprising," and "having," and any variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed, but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus.
Example 1
According to the embodiment of the application, an oil and gas pipeline stress monitoring and early warning system is provided. FIG. 1 is a schematic diagram of an oil and gas pipeline stress monitoring and early warning system provided according to an embodiment of the application. As shown in fig. 1, the system includes:
the multiple groups of sensors 102 are respectively arranged at multiple monitoring points of the pipeline and used for acquiring pipeline characteristic signals corresponding to the monitoring points, wherein the pipeline characteristic signals comprise stress characteristic signals and temperature characteristic signals.
Specifically, the monitoring points may be points that are arranged at fixed intervals on the pipeline, or may be points that are arranged on key sections of the pipeline. A group of sensors 102 are arranged at each monitoring point, and pipeline characteristic signals of the positions of the monitoring points are obtained, so that a data base is laid for stress monitoring of pipelines. Under the condition that each group of sensors 102 comprises a vibrating wire type strain sensor and a thermistor, the pipeline characteristic signals collected by the sensors comprise vibrating wire resonance frequency and resistance of the thermistor.
The data acquisition modules 104 are respectively arranged in the monitoring boxes of the monitoring piles, wherein each data acquisition module 104 is connected with the corresponding sensor 102 of at least one monitoring point, receives the pipeline characteristic signals acquired by the sensors 102 of at least one monitoring point, processes the received pipeline characteristic signals into monitoring data, and sends the monitoring data to the cloud server 106.
Specifically, the pipeline characteristic signal comprises a vibrating wire resonance frequency and a resistance value of the thermistor, and the pipeline characteristic signal is processed into monitoring data, wherein the monitoring data comprises strain data and temperature data. The data acquisition module 104 may be connected to a plurality of sensors 102 corresponding to one or more monitoring points, and acquire the pipeline characteristic signals transmitted by the sensors 102, then filter and amplify the pipeline characteristic signals through an internal signal filtering and amplifying circuit, and then upload the monitoring data to the cloud server 106 through the wireless communication module by the micro control unit after being processed by the analog-to-digital conversion circuit and the micro control unit.
The data acquisition module 104 is connected to the wireless communication module to upload the monitoring data to the cloud server 106.
And the cloud server 106 is in communication with the at least one data acquisition module 104 and is used for transmitting control instructions to the data acquisition module and receiving monitoring data.
And the monitoring platform 108 is in communication connection with the cloud server 106 and is used for acquiring monitoring data, determining the stress state of each monitoring point of the pipeline through the monitoring data and a stress state calculation model in the early warning model, determining an early warning level corresponding to the stress state through an early warning level table in the early warning model, and giving an alarm when the early warning level corresponding to the stress state exceeds a preset level, wherein the early warning level table is used for representing the corresponding relation between different early warning levels and different stress states.
The preset level may be a level which needs to be set to give an alarm in advance, for example, a yellow early warning may be set to be the preset level, and an alarm is given when the early warning level is the yellow early warning.
Specifically, the monitoring platform 108 may obtain strain data and temperature data from the cloud server 106, calculate an axial stress state of a cross section of the pipeline where each monitoring point is located through the collected data and a stress state calculation model, and determine an early warning level corresponding to the stress state through an early warning level table, where the early warning level table is shown in table 1:
TABLE 1
Wherein, β is a stress state, specifically, a percentage of a pipeline axial stress monitoring value in an axial allowable additional stress of the pipeline, when a group of acquired monitoring data sent by a certain monitoring point is calculated by a preset stress state calculation model, for example, the stress state of the monitoring point is 50%, it is determined that blue early warning is given, and no alarm is given; and when the obtained stress state is 90%, judging that the stress state is red early warning, and giving an alarm.
The oil and gas pipeline stress monitoring and early warning system provided by the embodiment of the application is respectively arranged at a plurality of monitoring points of a pipeline through a plurality of groups of sensors 102 and is used for collecting pipeline characteristic signals corresponding to the monitoring points, wherein the pipeline characteristic signals comprise stress characteristic signals and temperature characteristic signals; the system comprises at least one data acquisition module 104, at least one cloud server 106 and a monitoring server, wherein the data acquisition modules 104 are respectively arranged in monitoring boxes of the monitoring piles which are matched with each other, each data acquisition module 104 is connected with a sensor 102 corresponding to at least one monitoring point, receives pipeline characteristic signals acquired by the sensors 102 of the at least one monitoring point, processes the received pipeline characteristic signals into monitoring data, and sends the monitoring data to the cloud server 102; the cloud server 106 is in communication with the at least one data acquisition module 104 and is used for transmitting a control instruction to the data acquisition module 104 and receiving monitoring data; the monitoring platform 108 is in wireless communication connection with the cloud server 106 and is used for acquiring monitoring data, determining the stress state of each monitoring point of the pipeline through the monitoring data and a stress state calculation model in the early warning model, determining an early warning level corresponding to the stress state through an early warning level table in the early warning model, and giving an alarm when the early warning level corresponding to the stress state exceeds a preset level, wherein the early warning model comprises the stress state calculation model and the early warning level table, and the early warning level table is used for representing corresponding relations between different early warning levels and different stress states. The problem of can't monitor pipeline stress effectively in real time among the correlation technique, can't accurately judge the stress state of pipeline, and can't in time carry out the early warning to pipeline stress state anomaly is solved. Data are collected through a plurality of groups of sensors arranged at each monitoring point of the pipeline, and the stress state of the pipeline is judged and early warned by combining an early warning model, so that the monitoring, early warning and evaluation capabilities of the stress state of the oil-gas pipeline are effectively improved, and the safe operation effect of the oil-gas pipeline is guaranteed.
Optionally, in the oil and gas pipeline stress monitoring and early warning system that this application embodiment provided, every group sensor in the multiunit sensor includes: the strain sensors are arranged on the axial outer wall of the pipeline where the monitoring points are located and used for acquiring strain data of the monitoring points; wherein, be provided with a plurality of temperature sensor on every strain sensor for acquire the temperature data of monitoring point.
Optionally, in the oil and gas pipeline stress monitoring and early warning system that this application embodiment provided, the data acquisition module includes: the excitation signal generating circuit is used for exciting the vibrating wire type strain gauge to enable the vibrating wire type strain gauge to resonate with a pipeline; the signal conditioning circuit is connected with the vibrating wire type strain gauge and is used for receiving the resonance signal and filtering and amplifying the resonance signal; the analog-to-digital conversion circuit is connected with the signal conditioning circuit and is used for converting the analog signal into a digital signal; and the micro control unit is connected with the analog-to-digital conversion circuit and the excitation circuit and is used for processing and acquiring resonance frequency data and the resistance value of the thermistor, and controlling system excitation, acquisition, data transmission and the like.
Specifically, fig. 2 is a schematic diagram of an optional data acquisition module provided according to an embodiment of the present application, as shown in fig. 2: the micro control unit stores instructions recognizable by a computer, when the equipment receives an acquisition instruction sent by the platform, the micro control unit applies pulse frequency sweeping signals to the vibrating wire type strain gauge to enable the vibrating wire type strain gauge to resonate, the resonant signals are filtered and amplified through the signal conditioning circuit, then the resonant signals are converted into digital signals through the analog-to-digital conversion circuit, finally, the micro control unit processes and obtains resonant frequency and temperature data, the data are transmitted to the Aliskiu server through the 4G network, and the monitoring and early warning platform is connected with the server to remotely obtain the data.
Optionally, in the oil and gas pipeline stress monitoring and early warning system provided in the embodiment of the present application, further include: monitoring pile, including the support column, be provided with monitoring box, renewable energy power generation facility and orientation module on the support column, wherein, orientation module is used for confirming the positional information who monitors the pile, and the storage has data acquisition module and wireless communication module in the monitoring box, and renewable energy power generation facility includes the battery for to data acquisition and transmission module power supply, wireless communication module and data acquisition module are connected, in order to support the communication between data acquisition module and the cloud ware.
Specifically, the monitoring pile main body comprises a supporting column, a monitoring box and a renewable energy power generation device, wherein the monitoring box can be provided with a data acquisition module, a wireless communication module and a solar controller, so that the condition that electronic components are damaged in a severe environment to cause inaccurate monitoring data is avoided; renewable energy power generation facility can be solar panel for supply power to the electronic components in the monitoring box, improved clean energy's utilization.
Optionally, the application provides a remote real-time monitoring and early warning platform. The platform includes: the control unit is used for remotely controlling the monitoring equipment; the acquisition unit is used for acquiring stress data and temperature data of the multi-point pipeline sent by the data acquisition module and displaying the stress data and the temperature data of the multiple monitoring points; a storage unit for storing monitored stress, temperature data and other related information; the calculation unit is used for calculating each level of early warning threshold value corresponding to each monitoring point according to the stress state calculation model and the pipeline operation parameters; the judging unit judges the early warning level corresponding to the stress state of each monitoring point through the monitoring data and the early warning level table, wherein the early warning model consists of a stress state calculation model and an early warning level table; and the alarm unit is used for displaying the early warning level and giving an alarm prompt.
The following provides an alternative data acquisition and query method for implementing data acquisition and data query according to an embodiment of the present application. Fig. 3 is a flowchart of an alternative data collection and query method provided according to an embodiment of the present application, as shown in fig. 3:
after the program is operated, the user selects a remote real-time acquisition function or a historical data query function.
When a real-time acquisition mode is selected, TCP/IP communication is firstly configured according to user selection, wherein serial port communication is mainly used for field debugging equipment, TCP/IP communication is mainly used for remote real-time monitoring, and an IP address, an IMEI equipment number and a remote port of target equipment are selected according to requirements. And then, selecting a manual acquisition mode and a continuous acquisition mode, configuring parameters such as an early warning threshold value, an alarm threshold value, sampling time and the like according to actual requirements, and inputting a corresponding acquisition instruction in a command bar to start data acquisition of the target sensor. After the collection is started, the real-time data of the target monitoring point can be presented in a real-time monitoring interface of the monitoring platform in a graph mode by selecting the target monitoring point. When the monitoring platform detects that the stress state is abnormal, the alarm lamp on the interface can be lightened, the abnormal data is marked, and the early warning level is judged according to the early warning model. If a stop key is clicked, the software stops and returns to a mode selection state; instead, the software will continue to display the data in real time. The monitored data can be automatically stored in a preset database in the background running process of the program.
When the historical data query mode is selected, information can be screened by setting the queried channel number, the starting time, the ending time and other screening conditions, and only abnormal alarm data can be queried; after the operation is completed, the data can be displayed by clicking the query. Meanwhile, the user can also delete or adjust the data after the data is screened. When the stop button is clicked, the program can be exited and the mode selection state is returned, and finally, the program can be exited by clicking the exit.
Example 2
Fig. 4 is a schematic diagram of an optional oil and gas pipeline stress monitoring and early warning system structure provided according to an embodiment of the application, and as shown in fig. 4, the system includes a monitoring pile 1, a monitoring box 2, a solar panel 3, a vibrating string type strain sensor 4, a pipeline 5, a communication module 6, a data acquisition module 7, a solar controller 8, a monitoring platform 9 and a storage battery 10.
The vibrating wire type strain sensor 4 is connected with a data acquisition module 7 in the monitoring box 2 through a signal wire; the solar controller 8 is connected with the solar panel 3 and the data acquisition module 7 through cables, and the controller 8 is used for controlling the charging energy storage of the storage battery 10 and the operation of the data acquisition module 7; the wireless communication module 6 is connected with the data acquisition module 7 to realize remote communication between the equipment and the cloud server. The monitoring and early warning platform 9 is connected with the cloud server through a wireless network, acquires real-time monitoring data of the pipeline, presents the real-time monitoring data in an interface in a chart mode, judges and displays the stress state and the early warning level of the pipeline according to a preset early warning model, and gives an alarm when the early warning level exceeds the preset alarm level.
Example 3
According to the embodiment of the application, an oil and gas pipeline stress monitoring and early warning method is further provided. FIG. 5 is a flow chart of a method for monitoring and warning the stress of an oil and gas pipeline according to an embodiment of the application. As shown in fig. 5, the method includes:
step S502, remotely acquiring multiple groups of monitoring data monitored by the data acquisition module and corresponding to multiple monitoring points of the pipeline, wherein the monitoring data comprises strain data and temperature data.
Specifically, under the condition that each group of sensors 102 includes a vibrating wire type strain sensor and a thermistor, the monitoring data includes a vibrating wire resonance frequency signal and a resistance value of the thermistor, and the monitoring platform can acquire the monitoring data of each monitoring point sent by the data acquisition module in a wireless communication mode to obtain strain data and temperature data.
Step S504, determining an early warning model corresponding to each monitoring point according to the operation parameters of the pipeline and a group of monitoring data of each monitoring point, wherein the early warning model comprises a stress state calculation model and an early warning level table, and the early warning level table is used for representing corresponding relations between different early warning levels and different stress states.
And S506, processing the monitoring data of each monitoring point according to the stress state calculation model to obtain the stress states of the monitoring points, and determining the early warning level corresponding to the stress state of the monitoring point according to the early warning level table corresponding to each monitoring point.
Specifically, stress data and temperature data are input into a stress state calculation model, and the stress state of each monitoring point is calculated.
Specifically, the early warning model may be represented by a corresponding relationship table, for example, the early warning level of the stress state is determined by constructing an early warning level table, which is shown in table 1, in an optional implementation manner, when a certain set of monitoring data sent by a certain monitoring point is obtained, and after calculation by the stress state calculation model, the obtained stress state is 20%, it is determined as a green early warning; and when the obtained stress state is 80%, judging that the stress state is yellow early warning.
And step S508, displaying the stress state, the monitoring data and the early warning level of the monitoring points, and giving an alarm when the early warning level corresponding to the stress state exceeds a preset level.
Specifically, the preset level may be a preset warning that needs to be given off, for example, when the warning level is set to be yellow or higher, when the stress state calculated by the stress state calculation model is 50% for a certain set of acquired monitoring data sent by a certain monitoring point, it is determined as a blue warning, and no warning is given off, and when the stress state calculated is 90%, it is determined as a red warning, and a warning is given off.
It should be noted that, after the monitoring data is collected, the data collected in real time can be visually displayed in the monitoring platform in a form or a chart or the like, and the change trend and the data content of the monitoring data can be visually observed.
The method for monitoring and early warning the stress of the oil and gas pipeline provided by the embodiment of the application comprises the steps of remotely acquiring multiple groups of monitoring data corresponding to multiple monitoring points of the pipeline monitored by a data acquisition module, wherein the monitoring data comprise strain data and temperature data; determining an early warning model corresponding to each monitoring point according to the operation parameters of the pipeline and a group of monitoring data of each monitoring point, wherein the early warning model comprises a stress state calculation model and an early warning level table, and the early warning level table is used for representing the corresponding relation between different early warning levels and different stress states; processing the monitoring data of each monitoring point according to the stress state calculation model to obtain the stress states of the monitoring points, and determining the early warning level corresponding to the stress state of the monitoring point through the early warning level table corresponding to each monitoring point; and displaying the stress state, the monitoring data and the early warning level of the monitoring points, and giving an alarm when the early warning level corresponding to the stress state exceeds a preset level. The problem of can't monitor pipeline stress effectively in real time among the correlation technique, can't accurately judge the stress state of pipeline, and can't in time carry out the early warning to pipeline stress state anomaly is solved. Data are collected through a plurality of groups of sensors arranged at each monitoring point of the pipeline, and the stress state of the pipeline is judged and early warned by combining an early warning model, so that the monitoring, early warning and evaluation capabilities of the stress state of the oil-gas pipeline are effectively improved, and the safe operation effect of the oil-gas pipeline is guaranteed.
Optionally, the stress state calculation model is:
wherein beta is the stress state, namely the percentage of the pipeline axial stress monitoring value in the pipeline axial allowable additional stress, V sigma is the pipeline axial stress monitoring value, delta sigma is less than 0, pipeline compression is realized, delta sigma is more than or equal to 0, pipeline tension is realized, mu is the Poisson ratio of the pipe, and the Poisson ratio can be 0.3, P0The operation pressure is measured in MPa, d is the inner diameter of the pipeline and is measured in mm, t is the wall thickness of the pipeline and is measured in mm, alpha is the linear expansion coefficient of the pipeline and is measured in DEG C-1E is the elastic modulus of the pipe with the unit of GPa and T1The temperature of the pipe wall when the monitoring measure is taken is measured in DEG C0Is the initial temperature of the tube wall in degrees Celsius, P1Is the pipeline operating pressure, and has the unit of MPa, sigmasIs the minimum yield strength of the pipe, in MPa.
Specifically, the stress state calculation model is obtained by the following steps:
firstly, establishing a pipeline axial stress calculation model according to a time node taking a stress monitoring measure, wherein the model comprises the following steps:
σL＝σL0+Vσ (7)
in the formula: sigmaLThe axial stress of the pipeline after the stress monitoring measure is taken; sigmaL0The method comprises the following steps of (1) taking stress monitoring measures to obtain initial axial stress of the pipeline; v sigma is a pipeline axial stress monitoring value;
wherein, the initial axial stress of the pipeline during the stress monitoring measure is calculated firstly:
wherein mu is the Poisson's ratio of the pipe, and can be 0.3; p0The unit is MPa for the operating pressure when monitoring measures are taken; d is the inner diameter of the pipeline and the unit is mm; t is the wall thickness of the pipeline, and the unit is mm; alpha is the linear expansion coefficient of the pipe with the unit of DEG C-1(ii) a E is the elastic modulus of the pipe, and the unit is GPa; t is1The temperature of the pipe wall is measured in units of temperature; t is0Is the initial temperature of the tube wall in degrees celsius.
In the pipeline design specification, the pipeline stress should meet both the equivalent stress requirement and the axial stress requirement:
the equivalent stress requirement is as follows: the equivalent stress should be less than 0.9 times the minimum yield strength, i.e.:
wherein, P1For monitoring the operating pressure at a certain moment after the start of the operation, the unit is MPa, sigmasIs the minimum yield strength of the pipe, in MPa.
The axial stress requirement is as follows: the axial stress should be less than 0.9 times the minimum yield strength. Namely:
|σL|≤0.9σs (10)
and (3) respectively driving the formula (7) and the formula (8) into the formula (9) and the formula (10) to be connected in parallel to obtain a relational expression of the pipeline axial stress monitoring value:
according to the relation of the pipeline axial stress monitoring value in the formula (11), a stress early warning model based on the pipeline axial monitoring stress is established, and the stress early warning model is as follows:
in the formula: beta is the percentage of the pipeline axial stress monitoring value in the pipeline axial allowable additional stress; and the delta sigma is more than or equal to 0 for pipeline stretching, and the delta sigma is less than 0 for pipeline compression.
The stress state of a certain monitoring point of the pipeline can be obtained by substituting the obtained monitoring data and the pipeline operation parameters into the formula (12).
The following is an example of an alternative stress state provided according to an embodiment of the present application: to be provided with
The calculation process of the embodiment is described by taking an axial stress monitoring scene of an elastic laying section of the L360M steel-grade pipeline with the wall thickness at a certain ground surface displacement as an example. Table 2 shows the basic parameters of the pipeline:
TABLE 2
Monitoring data at a certain moment after stress monitoring measures are taken shows that the monitoring section is in a compression state, the maximum axial compressive stress is-120 MPa, namely V sigma is-120 MPa and is less than 0, and as V sigma is less than 0, then:
substituting β into equation (12) yields:
namely, the stress state is 46.3%, and the monitoring point can be obtained as a blue early warning through the early warning level table.
Optionally, the stress state and the monitoring data of the multiple monitoring points are displayed: determining a target monitoring point in the multiple monitoring points, and determining the number of a target sensor in the target monitoring point; and acquiring target characteristic data and a stress state corresponding to the target characteristic data from the monitoring data of the plurality of monitoring points according to the number of the target sensor to obtain the target data, and displaying the target data through a preset type chart, wherein the stress state is associated with the number of the corresponding sensor and the corresponding monitoring data.
Specifically, the target monitoring point may be a monitoring point that the user wants to visually monitor, each sensor is a monitoring channel on the monitoring point, the serial number of the sensor may be a channel number, the sensor corresponding to the target monitoring point may be selected by selecting the channel number, and the data acquired by the sensor is acquired, that is, the data is the target data.
After the target data is acquired, the target data can be visually displayed in a chart mode, and the latest acquired data is updated in real time, for example, the data value and the data trend are displayed through graphs such as a scatter diagram or a line diagram, so that the development trend is judged.
It should be noted that before determining the target monitoring point, the data acquisition and the equipment configuration of the monitoring module are also needed, and the relevant parameters of the TCP/IP communication mode are set first; then selecting an acquisition mode according to requirements, and configuring parameters such as a database, an early warning threshold value, an alarm threshold value, sampling time and the like; after the acquisition mode selection and the parameter setting are finished, the data acquisition of the target sensor can be started by inputting a corresponding acquisition instruction in the command bar.
After the collection is started, the real-time data of the target monitoring point can be presented in a real-time monitoring interface of the monitoring platform in a graph mode by selecting the target monitoring point. When the monitoring platform detects that the stress state is abnormal, the alarm lamp on the interface can be lightened, the abnormal data is marked, and the early warning level is judged according to the early warning model. The monitored data can be automatically stored in a preset database in the background running process of the program.
Optionally, the method further includes: the method comprises the following steps of displaying historical stress states and historical monitoring data of a plurality of monitoring points, wherein the steps comprise: screening according to query conditions, and displaying historical monitoring data, stress states and early warning levels of a plurality of monitoring points, wherein the query conditions at least comprise one of the following conditions: the number of the measuring point, the number of the sensor, the starting time, the ending time and the early warning level corresponding to the stress state; and screening historical monitoring data and historical stress states of a plurality of monitoring points of the pipeline according to the query conditions to obtain screened data, and displaying the screened data through a preset type chart.
Specifically, historical data can be inquired and displayed through a monitoring and early warning platform, and data screening is carried out through setting conditions such as monitoring point numbers, sensor numbers, early warning levels, starting time and ending time of target inquiry data to obtain target data; meanwhile, two data types of normal data and alarm data can be selected, and data of a required type is obtained through screening; and then clicking a query key on the interface, so that the data content can be displayed in the interface of the monitoring and early warning platform, and meanwhile, the target data can be modified and deleted.
Optionally, the alarming when the early warning level corresponding to the stress state exceeds a preset level includes: an alarm device arranged on the monitoring platform sends out an alarm signal; and/or sending an alarm notification message to the terminal equipment associated with the monitoring platform.
Specifically, when the monitoring and early warning platform monitors that the stress state is abnormal, the monitoring platform displays alarm content and corresponding monitoring points on a monitoring interface, and sends an alarm message to the mobile terminal, for example, a short message or an email, so that the effect of simultaneously notifying multiple scenes of the alarm message is achieved.
It should be noted that the steps illustrated in the flowcharts of the figures may be performed in a computer system such as a set of computer-executable instructions and that, although a logical order is illustrated in the flowcharts, in some cases, the steps illustrated or described may be performed in an order different than presented herein.
The embodiment of the application also provides a nonvolatile storage medium, wherein the nonvolatile storage medium comprises a stored program, and the program controls the equipment where the nonvolatile storage medium is located to execute the oil-gas pipeline stress monitoring and early warning method during running.
The embodiment of the application also provides an electronic device, which comprises a processor and a memory; the storage is stored with computer readable instructions, and the processor is used for operating the computer readable instructions, wherein the computer readable instructions execute a stress monitoring and early warning method for the oil and gas pipeline when running. The electronic device herein may be a server, a PC, a PAD, a mobile phone, etc.
As will be appreciated by one skilled in the art, embodiments of the present application may be provided as a method, system, or computer program product. Accordingly, 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, the present application may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The above are merely examples of the present application and are not intended to limit the present application. Various modifications and changes may occur to those skilled in the art. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application should be included in the scope of the claims of the present application.
Claims (10)
1. A stress monitoring and early warning method for an oil and gas pipeline is characterized by comprising the following steps:
the method comprises the steps of remotely acquiring multiple groups of monitoring data which are monitored by a data acquisition module and correspond to multiple monitoring points, wherein the monitoring data comprise strain data and temperature data;
determining an early warning model corresponding to the monitoring points according to the operation parameters of the pipeline and a group of monitoring data of each monitoring point, wherein the early warning model comprises a stress state calculation model and an early warning level table, and the early warning level table is used for representing corresponding relations between different early warning levels and different stress states;
processing the monitoring data of each monitoring point according to the stress state calculation model to obtain the stress states of the monitoring points, and determining the early warning level corresponding to the stress state of the monitoring point through the early warning level table corresponding to each monitoring point;
and displaying the stress state, the monitoring data and the early warning level of the monitoring points, and giving an alarm when the early warning level corresponding to the stress state exceeds a preset level.
2. The method of claim 1, wherein the stress state computational model is:
wherein beta is the stress state, V sigma is the monitoring value of the axial stress of the pipeline, delta sigma is more than or equal to 0 is the stretching of the pipeline, delta sigma is less than 0 is the compression of the pipeline, mu is the Poisson ratio of the pipe, P is0In order to take the operation pressure during the monitoring measure, d is the inner diameter of the pipeline, T is the wall thickness of the pipeline, alpha is the linear expansion coefficient of the pipe, E is the elastic modulus of the pipe, and T is1For the wall temperature, T, at which monitoring measures are taken0Is the initial temperature of the tube wall, P1For operating pressure of the pipe, σsIs the minimum yield strength of the pipe.
3. The method of claim 1, wherein said presenting stress states and monitoring data for said plurality of monitoring points comprises:
determining a target monitoring point in the multiple monitoring points, and determining the number of a target sensor in the target monitoring point;
and acquiring target characteristic data and a stress state corresponding to the target characteristic data from the monitoring data of the monitoring points according to the number of the target sensor to obtain the target data, and displaying the target data through a preset type chart, wherein the stress state is associated with the number of the corresponding sensor and the corresponding monitoring data.
4. The method of claim 1, further comprising: displaying historical stress states and historical monitoring data of the multiple monitoring points, wherein the steps comprise:
determining a query condition, wherein the query condition comprises at least one of: the number of the measuring point, the number of the sensor, the starting time, the ending time and the early warning level corresponding to the stress state;
and screening the historical monitoring data and the historical stress state of the multiple monitoring points of the pipeline according to the query condition to obtain screened data, and displaying the screened data through a preset type chart.
5. The method of claim 1, wherein alarming when the pre-warning level corresponding to the stress state exceeds a preset level comprises:
an alarm device arranged on the monitoring platform sends out an alarm signal;
and/or sending an alarm notification message to terminal equipment associated with the monitoring platform.
6. The utility model provides an oil and gas pipeline stress monitoring early warning system which characterized in that includes:
the system comprises a plurality of groups of sensors, a monitoring unit and a control unit, wherein the plurality of groups of sensors are respectively arranged at a plurality of monitoring points of a pipeline and are used for acquiring pipeline characteristic signals corresponding to the monitoring points, and the pipeline characteristic signals comprise stress characteristic signals and temperature characteristic signals;
the system comprises at least one data acquisition module, a cloud server and a monitoring server, wherein the data acquisition modules are respectively arranged in monitoring boxes of monitoring piles which are matched with each other, each data acquisition module is connected with a sensor corresponding to at least one monitoring point of the pipeline, receives the pipeline characteristic signals acquired by the sensor corresponding to the at least one monitoring point, processes the received pipeline characteristic signals into monitoring data, and sends the monitoring data to the cloud server;
the cloud server is communicated with the at least one data acquisition module and used for transmitting a control instruction to the data acquisition module and receiving the monitoring data;
the monitoring platform is in wireless communication connection with the cloud server and used for acquiring the monitoring data, determining the stress state of each monitoring point of the pipeline through the monitoring data and a stress state calculation model in an early warning model, determining the early warning level corresponding to the stress state through an early warning level table in the early warning model, and giving an alarm when the early warning level corresponding to the stress state exceeds a preset level, wherein the early warning level table is used for representing the corresponding relation between different early warning levels and different stress states.
7. The system of claim 6, wherein each of the plurality of sets of sensors comprises:
the strain sensors are arranged on the axial outer wall of the pipeline where the monitoring points are located and used for acquiring strain data of the monitoring points;
and each strain sensor is provided with a temperature sensor for acquiring temperature data of the monitoring point.
8. The system of claim 6, wherein the hydrocarbon pipeline stress monitoring and warning system further comprises:
the monitoring pile comprises a supporting column, wherein a monitoring box, a renewable energy power generation device and a positioning module are arranged on the supporting column, the positioning module is used for determining position information of the monitoring pile, a data acquisition module and a wireless communication module are arranged in the monitoring box, the renewable energy power generation device comprises a storage battery and is used for supplying power to the data acquisition module and the wireless communication module, and the wireless communication module is connected with the data acquisition module to support communication between the data acquisition module and the cloud server.
9. A non-volatile storage medium, characterized in that the non-volatile storage medium comprises a stored program, wherein the program controls a device where the non-volatile storage medium is located to execute the method according to any one of claims 1 to 5 when running.
10. An electronic device, comprising a processor and a memory, wherein the memory stores computer readable instructions, and the processor is used for executing the computer readable instructions, wherein the computer readable instructions execute the method for monitoring and warning the stress of the oil and gas pipeline according to any one of claims 1 to 5.
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