Method, system and equipment for monitoring running state of long-distance pipeline

Abstract

The invention provides a long-distance pipeline operation state monitoring method, system and device, relates to the technical field of long-distance pipeline monitoring, and aims to solve the technical problems that long-distance pipeline operation state monitoring is incomplete and low in accuracy. The long-distance pipeline operation state monitoring method comprises the steps that potential risk pipelines in long-distance pipelines are determined, and the potential risk pipelines in the long-distance pipelines are determined; generating a current pipeline fatigue damage value of the potential risk pipeline according to the pipeline operation state data of the potential risk pipeline; under the condition that the current pipeline fatigue damage value is smaller than the pipeline fatigue damage threshold value, an affiliated associated coupling facility of the potential risk pipeline is determined; according to the coupling pipeline operation data of the affiliated association coupling facility, generating a coupling pipeline influence factor of the affiliated association coupling facility; and determining an operation state monitoring result of the long-distance pipeline according to the coupling pipeline influence factor. According to the invention, the operation state of the long-distance pipeline can be accurately and comprehensively monitored.

Description

Technical Field

[0001] The present application relates to the technical field of long-distance pipeline monitoring, and in particular to a method, system, and device for monitoring the operating status of a long-distance pipeline. Background Art

[0002] Long-distance pipelines are often used to transport energy over vast distances, potentially reaching hundreds or even thousands of kilometers. The longer the distance, the more challenging their operation and management. Pipelines age over time and are susceptible to corrosion from media and other factors, leading to leaks. Therefore, accurately monitoring the operational status of long-distance pipelines is crucial to ensuring safe and stable operation.

[0003] Conventional technology typically relies on manual inspections to monitor the operation of long-distance pipelines. This approach can lead to significant resource consumption, low efficiency, and a high error rate. Conventional methods for monitoring the operation of long-distance pipelines typically rely on the pipeline's structural design, monitoring only the pipeline itself. This can lead to incomplete monitoring of the pipeline's operating status and low accuracy.

[0004] Therefore, how to accurately and comprehensively monitor the operating status of long-distance pipelines is a technical problem that needs to be solved at present. Summary of the Invention

[0005] The embodiments of the present application provide a method, system, and device for monitoring the operating status of a long-distance pipeline, aiming to solve the technical problem of incomplete and low accuracy monitoring of the operating status of a long-distance pipeline.

[0006] To achieve the above objectives, this application adopts the following technical solutions:

[0007] In a first aspect, a method for monitoring the operating status of a long-distance pipeline is provided, comprising: determining a potential risk pipeline in the long-distance pipeline, and generating a current pipeline fatigue damage value for the potential risk pipeline based on the pipeline operating status data of the potential risk pipeline; when the current pipeline fatigue damage value is less than a pipeline fatigue damage threshold, determining an affiliated associated coupling facility of the potential risk pipeline; the affiliated associated coupling facility being a pipeline segment to be inspected, obtained within a preset monitoring range centered on the potential risk pipeline; generating a coupled pipeline impact factor for the affiliated associated coupling facility based on the coupled pipeline operating data of the affiliated associated coupling facility; the coupled pipeline impact factor being used to indicate whether the affiliated associated coupling facility is abnormal; and determining an operating status monitoring result of the long-distance pipeline based on the coupled pipeline impact factor.

[0008] Optionally, identify potential risk pipelines in long-distance pipelines, including:

[0009] The historical pipeline operation data of pre-marked risk pipelines in the long-distance pipeline is obtained; the pre-marked risk pipelines are pre-set pipelines; and the long-distance pipeline includes multiple pre-marked risk pipelines.

[0010] The pipeline operation usage intensity value of the pre-marked risk pipeline is calculated based on the preset unit operation time and the historical pipeline operation data of the pre-marked risk pipeline; the pipeline operation usage intensity value is determined based on the unit operation time corresponding to the pipeline operation usage intensity value.

[0011] The pipeline operation intensity value within the pre-marked intensity range is determined to obtain the risk-marked intensity value. The pre-marked intensity is a pre-set intensity value for when the operation load of the pre-marked risk pipeline is large.

[0012] According to the risk mark usage intensity value, determine the pipeline usage fluctuation intensity value corresponding to the risk mark usage intensity value. The pipeline usage fluctuation intensity value satisfies the following formula:

[0013]

[0014] Among them, IF is the pipeline usage fluctuation intensity value, n1 is the number of risk mark usage intensity values, n2 is the total number of pipeline operation usage intensity values, Sui is the i-th risk mark usage intensity value, and ΔSus is the mean of the risk mark usage intensity values.

[0015] The pre-marked risk pipeline corresponding to the pipeline usage fluctuation intensity value greater than or equal to the usage intensity threshold is determined as a potential risk pipeline.

[0016] Optionally, the pipeline operation intensity value satisfies the following formula:

[0017]

[0018] Among them, Su is the pipeline operation intensity value, ΔTs 2 is the variance of the temperature values of each data sampling point outside the pre-marked risk pipeline within the unit operating time, p is the mean value of the pipeline pressure corresponding to each data sampling point inside the pre-marked risk pipeline within the unit operating time, D is the inner diameter of the pre-marked risk pipeline, k2 is the service loss coefficient of the pre-marked risk pipeline, k1 is the material compressive strength coefficient of the pre-marked risk pipeline, din is the thickness of the pre-marked risk pipeline, L is the length of the pre-marked risk pipeline, and a v is the average vibration acceleration of each data sampling point outside the pre-marked risk pipeline within the unit operating time, A is the pipeline cross-sectional area of the pre-marked risk pipeline, dex is the thickness of the barrier material attached to the outside of the pre-marked risk pipeline, and k3 is the barrier material coefficient of the barrier material attached to the outside of the pre-marked risk pipeline.

[0019] Optionally, the pipeline operation status data of the potential risk pipeline includes: pipeline internal pressure data, pipeline real-time vibration data, real-time temperature data, and post-repair status data; the current pipeline fatigue damage value of the potential risk pipeline is generated based on the pipeline operation status data of the potential risk pipeline, including:

[0020] The number of pressure load cycles is generated based on the internal pressure data of the pipeline; the theoretical comprehensive stress is determined based on the real-time vibration data and real-time temperature data of the pipeline. The theoretical comprehensive stress satisfies the following formula:

[0021]

[0022] Among them, St(t) is the theoretical comprehensive stress at time point t, λ is the reference stress weight coefficient, ΔT(t) is the temperature of the potential risk pipeline at time point t, Tref is the preset pipeline reference temperature, ce is the thermal expansion coefficient of the potential risk pipeline, ρ is the density of the potential risk pipeline, a(t) is the vibration acceleration of the potential risk pipeline at time point t, and St is the pipeline hardness coefficient of the potential risk pipeline.

[0023] The theoretical stress amplitude is determined based on the difference between the maximum and minimum values in the theoretical comprehensive stress; the theoretical stress amplitude is used to represent the range of stress variation of potential risk pipelines under cyclic loads.

[0024] According to the post-maintenance status data, the maintenance stress concentration factor is determined, and the maintenance stress concentration factor satisfies the following formula:

[0025]

[0026] Among them, K(t) is the maintenance stress concentration coefficient corresponding to time point t, Kt0 is the preset basic stress coefficient, β1 is the first proportional coefficient, h is the real-time bulge height of the maintenance weld of the potential risk pipeline, r is the transition fillet radius of the maintenance notch of the potential risk pipeline, β2 is the second proportional coefficient, Tcr(t) is the wear depth of the potential risk pipeline at time point t, Tcr0 is the preset initial wall thickness of the potential risk pipeline, β3 is the third proportional coefficient, p(t) is the internal pressure of the potential risk pipeline at time point t, p ms is the preset standard reference pressure, p ex (t) is the change in external environmental pressure of the potential risk pipeline at time point t.

[0027] The current pipeline fatigue damage value satisfies the following formula:

[0028]

[0029] Where CPF is the current pipeline fatigue damage value, N is the total number of categories of preset stress amplitude, Nj is the number of pressure load cycles under the j-th preset stress amplitude, NAj is the theoretical number of load cycles under the j-th preset stress amplitude, K(t) is the maintenance stress concentration factor corresponding to time point t, A fst is the theoretical stress amplitude.

[0030] Optionally, the subsidiary associated coupling facility is a pipeline section to be detected obtained within a preset monitoring range centered on the potential risk pipeline. When the current pipeline fatigue damage value is less than the pipeline fatigue damage threshold, determining the subsidiary associated coupling facility of the potential risk pipeline includes:

[0031] After applying a preset test excitation to the pipeline section to be inspected, the coupled vibration feedback result of the potential risk pipeline is obtained; the coupled vibration feedback result is obtained through the pipeline section to be inspected corresponding to the coupled vibration feedback result; the pipeline section to be inspected corresponding to the coupled vibration feedback result greater than or equal to the vibration feedback threshold is determined as an affiliated associated coupling facility.

[0032] Optionally, the coupled pipeline operation data includes: pressure fluctuation data and flow fluctuation data; the pressure fluctuation data includes vibration acceleration and vibration frequency of the attached associated coupled facility; the flow fluctuation data includes flow fluctuation amplitude; based on the coupled pipeline operation data of the attached associated coupled facility, generating a coupled pipeline impact factor of the attached associated coupled facility, including:

[0033] The coupling pipeline influence factor satisfies the following formula:

[0034]

[0035] Among them, CPF is the coupling pipeline influence factor, γ1 is the vibration influence coefficient, Ane is the vibration acceleration of the subsidiary associated coupling facility, ω is the vibration frequency of the subsidiary associated coupling facility, Fd is the vibration attenuation coefficient, Anom is the tolerance acceleration of the potential risk pipeline, γ2 is the flow influence coefficient, Qne is the flow fluctuation amplitude of the subsidiary associated coupling facility, Fv is the flow transfer attenuation coefficient, and Qnom is the standard flow fluctuation amplitude of the potential risk pipeline.

[0036] Optionally, the operation status monitoring results of the long-distance pipeline are determined based on the coupled pipeline influencing factors, including:

[0037] When the coupling pipeline impact factor is greater than or equal to the coupling pipeline impact threshold, the operation status monitoring result of the long-distance pipeline is determined to be an abnormality in the pipeline coupling facilities, and a pipeline coupling facility abnormality warning is generated, so that maintenance can be carried out according to the pipeline coupling facility abnormality warning; when the coupling pipeline impact factor is less than the coupling pipeline impact threshold, a risky pipeline operation safety instruction is determined, and the long-distance pipeline is continuously monitored according to the risky pipeline operation safety instruction.

[0038] Optionally, a method for monitoring the operating status of a long-distance pipeline further includes:

[0039] When the current pipeline fatigue damage value is greater than or equal to the pipeline fatigue damage threshold, a risk pipeline status abnormality warning is generated, so that maintenance can be carried out according to the risk pipeline status abnormality warning.

[0040] In a second aspect, a long-distance pipeline operation status monitoring system is provided, comprising:

[0041] The pipeline fatigue damage generation module is used to determine the potential risk pipelines in the long-distance pipeline and generate the current pipeline fatigue damage value of the potential risk pipeline based on the pipeline operation status data of the potential risk pipeline.

[0042] The coupling impact factor generation module is used to determine the associated coupling facilities of the potential risk pipeline and generate the coupling pipeline impact factor.

[0043] The coupling facility warning generation module is used to generate a pipeline coupling facility abnormality warning when it is determined that the operation status monitoring result of the long-distance pipeline is that the pipeline coupling facility is abnormal, so as to carry out maintenance according to the pipeline coupling facility abnormality warning.

[0044] In a third aspect, a long-distance pipeline operation status monitoring device is provided, which includes: a communication unit and a processing unit; the communication unit is used to determine a potential risk pipeline in a long-distance pipeline and generate a current pipeline fatigue damage value of the potential risk pipeline based on the pipeline operation status data of the potential risk pipeline.

[0045] The processing unit is used to determine the subsidiary associated coupling facilities of the potential risk pipeline when the current pipeline fatigue damage value is less than the pipeline fatigue damage threshold; the subsidiary associated coupling facilities are the pipeline sections to be detected obtained within a preset monitoring range with the potential risk pipeline as the center.

[0046] The processing unit is further configured to generate a coupling pipeline impact factor of the subsidiary associated coupling facility based on the coupling pipeline operation data of the subsidiary associated coupling facility; the coupling pipeline impact factor is used to indicate whether the subsidiary associated coupling facility is abnormal.

[0047] The processing unit is also used to determine the operation status monitoring result of the long-distance pipeline according to the coupling pipeline influencing factor.

[0048] In a fourth aspect, a long-distance pipeline operation status monitoring device is provided, comprising a memory and a processor; the memory is used to store computer-executable instructions, and the processor and the memory are connected via a bus; when the long-distance pipeline operation status monitoring device is running, the processor executes the computer-executable instructions stored in the memory, so that the long-distance pipeline operation status monitoring device performs the long-distance pipeline operation status monitoring method of the first aspect.

[0049] The long-distance pipeline operation status monitoring device can be an electronic device or a component within an electronic device, such as a chip system within the electronic device. The chip system is configured to support the electronic device in implementing the functions described in the first aspect and any possible implementation thereof, such as acquiring and determining the data and / or information involved in the long-distance pipeline operation status monitoring method. The chip system includes a chip and may also include other discrete components or circuit structures.

[0050] In a fifth aspect, a computer-readable storage medium is provided, the computer-readable storage medium including computer execution instructions. When the computer execution instructions are executed on a computer, the computer executes the long-distance pipeline operation status monitoring method described in the first aspect.

[0051] In a sixth aspect, a computer program product is also provided, which includes a computer program or instructions. When the computer instructions are executed on a long-distance pipeline operation status monitoring device, the long-distance pipeline operation status monitoring device executes the long-distance pipeline operation status monitoring method as described in the first aspect above.

[0052] It should be noted that the aforementioned computer instructions may be stored in whole or in part on a computer-readable storage medium. The computer-readable storage medium may be packaged together with the processor of the long-distance pipeline operation status monitoring device, or may be packaged separately from the processor of the long-distance pipeline operation status monitoring device, and this is not limited in the present embodiment.

[0053] The descriptions of the second, third, fourth, fifth and sixth aspects of this application can refer to the detailed description of the first aspect.

[0054] In the embodiments of this application, the name of the long-distance pipeline operation status monitoring device does not limit the device or functional modules themselves. In actual implementation, these devices or functional modules may appear with other names. For example, the processing unit may also be called a processing module, a processor, etc. As long as the functions of each device or functional module are similar to those of this application, they are within the scope of the claims of this application and their equivalents.

[0055] The technical solution provided by this application brings at least the following beneficial effects:

[0056] Based on any of the above aspects, an embodiment of the present application provides a method for monitoring the operating status of a long-distance pipeline, comprising: first, determining a potential risk pipeline in a long-distance pipeline, and generating a current pipeline fatigue damage value of the potential risk pipeline based on the pipeline operating status data of the potential risk pipeline. Then, when the current pipeline fatigue damage value is less than the pipeline fatigue damage threshold, determining the subsidiary associated coupling facility of the potential risk pipeline. The subsidiary associated coupling facility is a pipeline section to be detected that is obtained within a preset monitoring range with the potential risk pipeline as the center. Then, based on the coupled pipeline operating data of the subsidiary associated coupling facility, a coupled pipeline influence factor of the subsidiary associated coupling facility is generated (the coupled pipeline influence factor is used to indicate whether the subsidiary associated coupling facility is abnormal). Subsequently, the operating status monitoring result of the long-distance pipeline is determined based on the coupled pipeline influence factor.

[0057] As can be seen from the above, firstly, this application can monitor the operating status and abnormality of potential risk pipelines by identifying potential risk pipelines in long-distance pipelines and generating current pipeline fatigue damage based on the pipeline operating status data of potential risk pipelines. This avoids the problem of large resource consumption caused by monitoring the entire long-distance pipeline due to its long distance. Focusing on the monitoring and subsequent maintenance of potential risk pipelines in long-distance pipelines can improve the resource utilization of long-distance pipelines and improve the accuracy of long-distance pipeline monitoring.

[0058] Secondly, if the current fatigue damage value of a potential risk pipeline is less than the pipeline fatigue damage threshold, the system obtains the associated coupled facilities within a preset range centered on the potential risk pipeline—that is, other facilities that may be affected by the potential risk pipeline—and generates an impact factor for the coupled pipeline. By detecting anomalies in these associated coupled facilities, the system avoids the common practice of monitoring only the monitored pipeline itself while ignoring other facilities affected by the monitored pipeline due to inter-pipeline interactions. This can lead to incomplete and inaccurate long-distance pipeline operation monitoring.

[0059] The beneficial effects of the first, second, third, fourth, fifth and sixth aspects of this application can all be referred to the analysis of the above beneficial effects, and will not be repeated here. BRIEF DESCRIPTION OF THE DRAWINGS

[0060] Figure 1 A schematic diagram of the structure of a long-distance pipeline operation status monitoring system provided in an embodiment of the present application;

[0061] Figure 2 A schematic diagram of the hardware structure of a long-distance pipeline operation status monitoring device provided in an embodiment of the present application;

[0062] Figure 3 A flow chart of a method for monitoring the operating status of a long-distance pipeline provided in an embodiment of the present application;

[0063] Figure 4 A flow chart of another method for monitoring the operating status of a long-distance pipeline provided in an embodiment of the present application;

[0064] Figure 5 A flow chart of another method for monitoring the operating status of a long-distance pipeline provided in an embodiment of the present application;

[0065] Figure 6 A flow chart of another method for monitoring the operating status of a long-distance pipeline provided in an embodiment of the present application;

[0066] Figure 7 A flow chart of another method for monitoring the operating status of a long-distance pipeline provided in an embodiment of the present application;

[0067] Figure 8 A schematic diagram of the structure of a long-distance pipeline operation status monitoring device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0068] The following will be combined with the drawings in the embodiments of this application to clearly and completely describe the technical solutions in the embodiments of this application. Obviously, the embodiments described are only part of the embodiments of this application, not all of the embodiments. Based on the embodiments in this application, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of this application.

[0069] It should be noted that in the embodiments of this application, words such as "exemplary" or "for example" are used to indicate examples, illustrations, or descriptions. Any embodiment or design described as "exemplary" or "for example" in the embodiments of this application should not be interpreted as being more preferred or advantageous over other embodiments or designs. Rather, the use of words such as "exemplary" or "for example" is intended to present the relevant concepts in a concrete manner.

[0070] In order to facilitate a clear description of the technical solutions of the embodiments of the present application, in the embodiments of the present application, words such as "first" and "second" are used to distinguish between identical or similar items with basically the same functions and effects. Those skilled in the art can understand that words such as "first" and "second" do not limit the quantity and execution order.

[0071] Before giving a detailed introduction to the long-distance pipeline operation status monitoring method provided by this application, a brief introduction to the application scenarios and implementation environment involved in this application is first given.

[0072] First, a brief introduction to the application scenarios involved in this application is given.

[0073] As described in the background, long-distance pipelines are often used to transport energy over long distances. The longer the distance, the more challenging their operation and management. Furthermore, over time, long-distance pipelines gradually age, leading to leaks and other issues. Therefore, monitoring the operational status of long-distance pipelines is necessary to ensure their proper operation. Conventional methods for monitoring the operational status of long-distance pipelines suffer from high resource consumption, low accuracy, and incomplete monitoring methods. Therefore, accurately and comprehensively monitoring the operational status of long-distance pipelines is a technical challenge that currently needs to be addressed.

[0074] In response to the above-mentioned problems, an embodiment of the present application provides a method for monitoring the operating status of a long-distance pipeline, comprising: first, determining a potential risk pipeline in a long-distance pipeline, and generating a current pipeline fatigue damage value of the potential risk pipeline based on the pipeline operating status data of the potential risk pipeline. Then, when the current pipeline fatigue damage value is less than the pipeline fatigue damage threshold, determining the subsidiary associated coupling facilities of the potential risk pipeline. The subsidiary associated coupling facilities are pipeline sections to be detected that are obtained within a preset monitoring range with the potential risk pipeline as the center. Then, based on the coupled pipeline operating data of the subsidiary associated coupling facilities, a coupled pipeline influence factor of the subsidiary associated coupling facilities is generated (the coupled pipeline influence factor is used to indicate whether the subsidiary associated coupling facilities are abnormal). Subsequently, the operating status monitoring results of the long-distance pipeline are determined based on the coupled pipeline influence factor.

[0075] As can be seen from the above, firstly, this application can monitor the operating status and abnormality of potential risk pipelines by identifying potential risk pipelines in long-distance pipelines and generating current pipeline fatigue damage based on the pipeline operating status data of potential risk pipelines. This avoids the problem of large resource consumption caused by monitoring the entire long-distance pipeline due to its long distance. Focusing on the monitoring and subsequent maintenance of potential risk pipelines in long-distance pipelines can improve the resource utilization of long-distance pipelines and improve the accuracy of long-distance pipeline monitoring.

[0076] Secondly, if the current fatigue damage value of a potential risk pipeline is less than the pipeline fatigue damage threshold, the system obtains the associated coupled facilities within a preset range centered on the potential risk pipeline—that is, other facilities that may be affected by the potential risk pipeline—and generates an impact factor for the coupled pipeline. By detecting anomalies in these associated coupled facilities, the system avoids the common practice of monitoring only the monitored pipeline itself while ignoring other facilities affected by the monitored pipeline due to inter-pipeline interactions. This can lead to incomplete and inaccurate long-distance pipeline operation monitoring.

[0077] The implementation environment of the above-mentioned long-distance pipeline operation status monitoring method can be the long-distance pipeline operation status monitoring system of the embodiment of the present application.

[0078] Figure 1 This is a schematic diagram of the structure of a long-distance pipeline operation status monitoring system provided in an embodiment of the present application. Figure 1 As shown, the long-distance pipeline operation status monitoring system includes: a long-distance pipeline operation status monitoring device 101 and a data storage device 102.

[0079] The long-distance pipeline operation status monitoring device 101 includes: a pipeline fatigue damage generation module 103 , a coupling impact factor generation module 104 and a coupling facility early warning generation module 105 .

[0080] Specifically, the long-distance pipeline operation status monitoring device 101 and the data storage device 102 are communicatively connected.

[0081] Specifically, the pipeline fatigue damage generation module 103 is in communication with the coupling impact factor generation module 104. The coupling impact factor generation module 104 is in communication with the coupling facility warning generation module 105.

[0082] In practical applications, the long-distance pipeline operation status monitoring device 101 can be connected to any number of data storage devices 102, and the long-distance pipeline operation status monitoring device 101 can be connected to any number of data acquisition devices 103. For ease of understanding, Figure 1 An example is given in which a long-distance pipeline operation status monitoring device 101 is connected to a data storage device 102 .

[0083] In the embodiment of the present application, the data storage device 102 is used to store the long-distance pipeline operation status data so that the long-distance pipeline operation status monitoring device 101 can monitor the operation status of the long-distance pipeline according to the long-distance pipeline operation status data.

[0084] In this embodiment of the present application, the pipeline fatigue damage generation module 103 is used to identify potential risk pipelines in a long-distance pipeline and generate a current pipeline fatigue damage value for the potential risk pipeline based on the pipeline operating status data of the potential risk pipeline. If the current pipeline fatigue damage value is less than the pipeline fatigue damage threshold, the coupling impact factor generation module 104 is used to identify the associated coupled facilities of the potential risk pipeline identified in the pipeline fatigue damage generation module 103 and generate a coupled pipeline impact factor. If the coupled pipeline impact factor generated by the coupling impact factor generation module 104 is greater than or equal to the coupled pipeline impact threshold, the coupling facility warning generation module 105 generates a pipeline coupled facility abnormality warning, allowing maintenance to be performed based on the pipeline coupled facility abnormality warning.

[0085] Optionally, the physical device of the long-distance pipeline operation status monitoring device 101 can be a server, a terminal, or other types of electronic devices, which is not limited in the embodiment of the present application.

[0086] Optionally, the terminal may be a device that provides voice and / or data connectivity to a user, a handheld device with wireless connection capabilities, or other processing devices connected to a wireless modem. A wireless terminal may communicate with one or more core networks via a radio access network (RAN). A wireless terminal may be a mobile terminal, such as a mobile phone (or "cellular" phone) and a computer with a mobile terminal, or a portable, pocket-sized, handheld, computer-built-in, or vehicle-mounted mobile device that exchanges voice and / or data with a radio access network, such as a mobile phone, tablet computer, laptop computer, netbook, or personal digital assistant (PDA).

[0087] Optionally, the above-mentioned server can be a server in a server cluster (consisting of multiple servers), or a chip in the server, or a system on a chip in the server, or can be implemented through a virtual machine (VM) deployed on a physical machine. This embodiment of the present application does not limit this.

[0088] Optionally, the long-distance pipeline operation status monitoring device 101 and the data storage device 102 may be two independent devices, or they may be integrated into the same device. When the long-distance pipeline operation status monitoring device 101 and the data storage device 102 are integrated into the same device, the data storage device 102 may be a storage module (e.g., a database, etc.) of the long-distance pipeline operation status monitoring device 101.

[0089] It is easy to understand that when the long-distance pipeline operation status monitoring device 101 and the data storage device 102 are integrated into the same device, the communication method between the long-distance pipeline operation status monitoring device 101 and the data storage device 102 is communication between the internal modules of the device. In this case, the communication process between the long-distance pipeline operation status monitoring device 101 and the data storage device 102 is the same as the communication process between the long-distance pipeline operation status monitoring device 101 and the data storage device 102 when they are independent.

[0090] For ease of understanding, this application is explained by taking the example that the long-distance pipeline operation status monitoring device 101 and the data storage device 102 are independent of each other.

[0091] The long-distance pipeline operation status monitoring device 101 in the long-distance pipeline operation status monitoring system includes the following Figure 2 The following are the components included. Figure 2Taking the long-distance pipeline operation status monitoring device shown as an example, the hardware structure of the long-distance pipeline operation status monitoring device 101 is introduced.

[0092] Figure 2 A schematic diagram of the hardware structure of a long-distance pipeline operation status monitoring device provided in an embodiment of the present application. The long-distance pipeline operation status monitoring device includes a processor 21, a memory 22, a communication interface 23, and a bus 24. The processor 21, the memory 22, and the communication interface 23 can be connected via the bus 24.

[0093] Processor 21 is the control center of the long-distance pipeline operation status monitoring device. It can be a single processor or a collective term for multiple processing elements. For example, processor 21 can be a general-purpose central processing unit (CPU) or other general-purpose processor. The general-purpose processor can be a microprocessor or any conventional processor.

[0094] As an embodiment, the processor 21 may include one or more CPUs, such as Figure 2 CPU0 and CPU1 are shown in the figure.

[0095] The memory 22 may be a read-only memory (ROM) or other type of static storage device that can store static information and instructions, a random access memory (RAM) or other type of dynamic storage device that can store information and instructions, an electrically erasable programmable read-only memory (EEPROM), a disk storage medium or other magnetic storage device, or any other medium that can be used to carry or store desired program code in the form of instructions or data structures and can be accessed by a computer, but is not limited thereto.

[0096] In one possible implementation, memory 22 can exist independently of processor 21 and can be connected to processor 21 via bus 24 to store instructions or program code. When processor 21 calls and executes the instructions or program code stored in memory 22, the long-distance pipeline operation status monitoring method provided in the following embodiments of this application can be implemented.

[0097] In the embodiment of the present application, the long-distance pipeline operation status monitoring device has different software programs stored in the memory 22, so the long-distance pipeline operation status monitoring device implements different functions. The functions performed by each device will be described in conjunction with the following flowchart.

[0098] In another possible implementation, the memory 22 may also be integrated with the processor 21 .

[0099] The communication interface 23 is used to connect the long-distance pipeline operation status monitoring device to other devices via a communication network. The communication network can be Ethernet, wireless access network, wireless local area network (WLAN), etc. The communication interface 23 can include a receiving unit for receiving data and a sending unit for sending data.

[0100] The bus 24 may be an ISA bus, a PCI bus, or an EISA bus. The bus may be divided into an address bus, a data bus, a control bus, and the like. For ease of presentation, Figure 2 Only one thick line is used in the diagram, but this does not mean that there is only one bus or one type of bus.

[0101] It should be pointed out that Figure 2 The structure shown in the figure does not constitute a limitation on the long-distance pipeline operation status monitoring device. Figure 2 In addition to the components shown, the long-distance pipeline operation status monitoring device may include more or fewer components than shown, or combine certain components, or arrange the components differently.

[0102] The following is a detailed introduction to the long-distance pipeline operation status monitoring method provided in the embodiments of the present application with reference to the accompanying drawings.

[0103] The long-distance pipeline operation status monitoring method provided in the embodiment of the present application is applied to Figure 1 The long-distance pipeline operation status monitoring device 101 in the long-distance pipeline operation status monitoring system shown in FIG. Figure 3 As shown, the long-distance pipeline operation status monitoring method provided in the embodiment of the present application includes:

[0104] S301: Determine a potential risk pipeline in a long-distance pipeline, and generate a current pipeline fatigue damage value of the potential risk pipeline based on pipeline operation status data of the potential risk pipeline.

[0105] Specifically, the long-distance pipeline operation status monitoring equipment first identifies potentially risky pipelines within the pipeline and then monitors the operating status of the acquired potentially risky pipelines, thereby achieving overall monitoring of the pipeline. During this process, the long-distance pipeline operation status monitoring equipment determines the corresponding current pipeline fatigue damage value based on the operating status data of the potentially risky pipeline. It then determines whether the current pipeline fatigue damage value corresponds to the pipeline fatigue damage threshold and, therefore, whether the current state of the potentially risky pipeline requires an early warning.

[0106] Optionally, the current pipeline fatigue damage indicates the fatigue degree suffered by the potential risk pipeline in the current operating state.

[0107] It can be seen that the long-distance pipeline operation status monitoring method provided in the embodiment of the present application, first of all, in order to reduce the monitoring cost of the long-distance pipeline, does not adopt the method of monitoring the entire long-distance pipeline. Instead, it focuses on monitoring by screening out potential risk pipelines in the long-distance pipeline that have greater pipeline risks and faster risk monitoring. By concentrating limited monitoring resources on monitoring and maintenance of high-risk pipelines, the resource utilization efficiency of the long-distance pipeline can be improved, and the problems of human monitoring in general technology resulting in large consumption of monitoring resources, low monitoring efficiency, and high error rate can be solved.

[0108] Next, the operating status of the potentially risky pipeline is monitored and its operating status data is obtained. Status analysis is then performed. The specific analysis process involves generating current pipeline fatigue damage based on the pipeline operating status data. Current pipeline fatigue damage represents the degree of fatigue experienced by the potentially risky pipeline under its current operating conditions. Whether the current pipeline fatigue damage is greater than or equal to the pipeline fatigue damage threshold is then determined to determine whether the current status of the potentially risky pipeline requires an early warning.

[0109] S302: When the current pipeline fatigue damage value is less than the pipeline fatigue damage threshold, determine the associated coupling facilities of the potential risk pipeline.

[0110] Among them, the subsidiary associated coupling facilities are the pipeline sections to be inspected that are obtained within the preset monitoring range with the potential risk pipeline as the center.

[0111] Specifically, when the current pipeline fatigue damage value is less than the pipeline fatigue damage threshold, the long-distance pipeline operation status monitoring equipment needs to determine the subsidiary associated coupling facilities of the potential risk pipeline, so as to achieve further monitoring of the long-distance pipeline operation status.

[0112] It can be seen that when the current pipeline fatigue damage value is less than the pipeline fatigue damage threshold, other pipelines and facilities that are coupled with the potential risk pipeline may have an impact on the potential risk pipeline. In order to conduct a comprehensive status assessment of the potential risk pipeline, the long-distance pipeline operation status monitoring equipment further determines the subsidiary associated coupling facilities of the potential risk pipeline.

[0113] S303: Generate coupling pipeline impact factors of the subsidiary-associated coupling facilities according to the coupling pipeline operation data of the subsidiary-associated coupling facilities.

[0114] Among them, the coupling pipeline impact factor is used to indicate whether the subsidiary associated coupling facilities are abnormal.

[0115] Specifically, the long-distance pipeline operation status monitoring device determines the coupling pipeline impact factor of the attached associated coupling facility by obtaining the coupled pipeline operation data of the attached associated coupling facility, so that the subsequent long-distance pipeline operation status monitoring device can judge whether there is any abnormality in the operation of the long-distance pipeline based on the coupled pipeline impact factor.

[0116] Optionally, the coupled pipeline impact factor represents the degree of influence of the associated coupled facilities on the potential risk pipeline.

[0117] S304. Determine the operation status monitoring result of the long-distance pipeline according to the coupling pipeline influencing factor.

[0118] Specifically, the long-distance pipeline operation status monitoring device determines the long-distance pipeline operation status monitoring result by judging whether the coupling pipeline influence factor is greater than or equal to the coupling pipeline influence threshold.

[0119] It can be seen that the embodiments of the present application achieve further monitoring of the operating status of long-distance pipelines by acquiring the subsidiary associated coupling facilities of the potential risk pipeline and monitoring the operating status of the subsidiary associated coupling facilities, thereby solving the problems of incomplete pipeline operation monitoring and low pipeline operation monitoring accuracy caused by the general technology of only monitoring the pipeline itself and ignoring other facilities that interact with the pipeline and have an impact on the operation of the pipeline.

[0120] In some embodiments, combined Figure 3 ,like Figure 4 As shown, in the above S301, determining the potential risk pipeline in the long-distance pipeline specifically includes:

[0121] S401: Acquire historical pipeline operation data of pre-marked risk pipelines in long-distance pipelines.

[0122] The pre-marked risk pipeline is a pre-set pipeline. Long-distance pipelines include multiple pre-marked risk pipelines.

[0123] Specifically, in order to subsequently obtain potential risk pipelines, the long-distance pipeline operation status monitoring equipment needs to first obtain pre-marked risk pipelines that are prone to pipeline abnormalities, and then obtain the historical pipeline operation data of the pre-marked risk pipelines, so as to subsequently perform risk analysis on the pre-marked risk pipelines based on the historical pipeline operation data of the pre-marked risk pipelines.

[0124] Optionally, the pre-marked risky pipeline is a conventional pipeline area or pipeline section that is prone to pipeline anomalies.

[0125] For example, pre-marked risky pipelines may include pipelines located in densely populated areas, environmentally sensitive areas, and near critical facilities. Densely populated areas include those near cities, towns, schools, and hospitals. Environmentally sensitive areas include nature reserves, water sources, and important agricultural areas. Pipelines near critical facilities include highways, railways, bridges, and power stations.

[0126] Pre-marked risk pipelines can also include pipelines laid in highly corrosive areas such as rivers, lakes, and sea crossing points; pipelines laid in areas with large terrain undulations such as hillsides and valleys. Such areas may have problems such as soil movement and erosion, which may easily affect the stability of the pipeline.

[0127] Pre-marked risk pipelines can also include pipe elbows, tees, reducers and other parts, which are prone to stress concentration and cause fatigue damage.

[0128] Pre-marked risk pipelines may also include pipelines laid through areas with large temperature differences, such as from high-temperature areas to low-temperature areas, which may cause changes in pipeline material properties and stress changes.

[0129] S402: Calculate the pipeline operation usage intensity value of the pre-marked risk pipeline according to the preset unit operation time and the historical pipeline operation data of the pre-marked risk pipeline.

[0130] The pipeline operation and usage intensity value is determined based on the unit operation time corresponding to the pipeline operation and usage intensity value.

[0131] Specifically, the preset unit operating time is used as the data division unit, and the historical pipeline operation data is divided, so that the pipeline operation usage intensity of the pre-marked risk pipeline in each unit operating time is determined by the unit operating time and the historical pipeline operation data.

[0132] Optionally, historical pipeline operation data is divided into multiple groups using a preset unit of operation time as the data division unit. The corresponding pipeline operation intensity is calculated based on the historical pipeline operation data in each group. Therefore, the acquired historical pipeline operation data for the pre-marked risk pipeline includes multiple pipeline operation intensities, each of which is the pipeline operation intensity for the preset unit of operation time.

[0133] S403: Determine the pipeline operation intensity value within the pre-marked intensity range to obtain a risk marked intensity value.

[0134] The pre-marking intensity is a pre-set intensity value when the operating load of the pre-marked risk pipeline is large.

[0135] Specifically, the pipeline operation usage intensity is extracted through the pre-marked pre-marked intensity range, thereby obtaining the risk-marked usage intensity.

[0136] Optionally, the pre-marked intensity range is a pre-set intensity for when the operating load of the pre-marked risk pipeline is high. Using the pre-marked intensity range can more quickly identify pipeline operating intensities with greater risks. Therefore, the pre-marked intensity range is used to extract pipeline operating intensities.

[0137] S404. Determine, according to the risk mark usage intensity value, a pipeline usage fluctuation intensity value corresponding to the risk mark usage intensity value.

[0138] The pipeline usage fluctuation intensity value satisfies the following formula:

[0139]

[0140] Among them, IF is the pipeline usage fluctuation intensity value, n1 is the number of risk mark usage intensity values, n2 is the total number of pipeline operation usage intensity values, Sui is the i-th risk mark usage intensity value, and ΔSus is the mean of the risk mark usage intensity values.

[0141] From the above formula, we can see that Indicates the ratio of risk mark usage intensity to the total pipeline operation usage intensity. It represents the sum of the differences between the intensity of each risk marker usage and the mean of the intensity of risk marker usage.

[0142] S405: Determine the pre-marked risk pipeline corresponding to the pipeline usage fluctuation intensity value greater than or equal to the usage intensity threshold as a potential risk pipeline.

[0143] Optionally, by comparing the pipeline usage fluctuation intensity value determined in the above step S404 with the usage intensity threshold, the usage fluctuation intensity value greater than or equal to the usage intensity threshold is screened out, and the corresponding pre-marked risk pipeline is used as the potential risk pipeline.

[0144] Optionally, the potential risk pipeline is a risk pipeline that has been repaired.

[0145] In some embodiments, the pipeline operation intensity value satisfies the following formula:

[0146]

[0147] Among them, Su is the pipeline operation intensity value, ΔTs 2 is the variance of the temperature values of each data sampling point outside the pre-marked risk pipeline within the unit operating time, p is the mean value of the pipeline pressure corresponding to each data sampling point inside the pre-marked risk pipeline within the unit operating time, D is the inner diameter of the pre-marked risk pipeline, k2 is the service loss coefficient of the pre-marked risk pipeline, k1 is the material compressive strength coefficient of the pre-marked risk pipeline, din is the thickness of the pre-marked risk pipeline, L is the length of the pre-marked risk pipeline, and a v is the average vibration acceleration of each data sampling point outside the pre-marked risk pipeline within the unit operating time, A is the pipeline cross-sectional area of the pre-marked risk pipeline, dex is the thickness of the barrier material attached to the outside of the pre-marked risk pipeline, and k3 is the barrier material coefficient of the barrier material attached to the outside of the pre-marked risk pipeline.

[0148] Optionally, the pipeline operation intensity is data indicating the pressure experienced by the pipeline during past operation. By calculating the pipeline operation intensity, the pressure experienced by the pre-marked risk pipeline under the influence of actual environment and operation can be obtained.

[0149] Optionally, the vibration acceleration average a of each data sampling point outside the pre-marked risk pipeline within the unit operating time v Used to indicate the vibration conditions to which the pre-marked risk pipeline is subjected during operation.

[0150] For example, when obtaining the data used in the above formula, for example, the variance ΔTs of the temperature value of each data sampling point outside the pre-marked risk pipeline within the unit operating time is 2When the mean value p of the pipeline pressure corresponding to each data sampling point within the pre-marked risk pipeline within the unit operating time is calculated, first, the data sampling points can be set in advance within the unit operating time to achieve refined data processing, and a temperature sampling sensor can be set outside the pre-marked risk pipeline to obtain the temperature value, and a pressure sensor can be set to detect the pipeline pressure of the pre-marked risk pipeline. Then, the variance ΔTs of the temperature value of each data sampling point outside the pre-marked risk pipeline within the unit operating time is calculated. 2 And the mean value p of the pipeline pressure corresponding to each data sampling point inside the pre-marked risk pipeline within the unit operating time.

[0151] The inner diameter D of the pre-marked risk pipe can be pre-set based on the basic conditions of the pre-marked risk pipe. The service life loss coefficient k2 of the pre-marked risk pipe can be determined based on the time the pre-marked risk pipe has been in service. The longer the service life, the greater the service life loss coefficient. The material compressive strength coefficient k1 can be pre-set based on the compressive strength of the pre-marked risk pipe material.

[0152] The thickness din of the pre-marked risk pipe and the length L of the pre-marked risk pipe can both be obtained by pre-measurement.

[0153] It can be understood that for pre-marked risk pipelines, barrier materials are also provided. The barrier materials have the function of bearing part of the operating pressure. Therefore, the pipeline operation intensity is comprehensively calculated by combining the thickness dex of the barrier material attached to the outside of the pre-marked risk pipeline and the barrier material coefficient k3 of the barrier material attached to the outside of the pre-marked risk pipeline.

[0154] In some embodiments, combined Figure 3 ,like Figure 5 As shown, in the above S301, the pipeline operation status data of the potential risk pipeline includes: pipeline internal pressure data, pipeline real-time vibration data, real-time temperature data and post-repair status data. The current pipeline fatigue damage value of the potential risk pipeline is generated based on the pipeline operation status data of the potential risk pipeline, including:

[0155] S501: Generate the number of pressure load cycles according to the internal pressure data of the pipeline.

[0156] Optionally, the number of pressure load cycles represents the actual number of stress cycles experienced by the potential risk pipeline under various preset stress amplitudes.

[0157] For example, when obtaining the number of pressure load cycles, the time domain data detected by the pressure sensor can be used first, and then the number of cycles under different stress amplitudes can be counted through rain flow counting or peak-valley statistics.

[0158] The pressure sensor can also be replaced with a stress sensor. The stress sensor or pressure sensor needs to be tightly fixed on the pipe wall during installation to ensure consistency with the stress transfer of the pipe and avoid inaccurate measurement results due to installation errors.

[0159] Then, according to the length of the pipeline, distribute as many sensors as possible to ensure that the pipeline is covered over as large an area as possible, so that the detection data is more consistent with the actual situation.

[0160] S502: Determine theoretical comprehensive stress based on real-time pipeline vibration data and real-time temperature data.

[0161] The theoretical comprehensive stress satisfies the following formula:

[0162]

[0163] Among them, St(t) is the theoretical comprehensive stress at time point t, λ is the reference stress weight coefficient, ΔT(t) is the temperature of the potential risk pipeline at time point t, Tref is the preset pipeline reference temperature, ce is the thermal expansion coefficient of the potential risk pipeline, ρ is the density of the potential risk pipeline, a(t) is the vibration acceleration of the potential risk pipeline at time point t, and St is the pipeline hardness coefficient of the potential risk pipeline.

[0164] From the above formula, we know that 1-λ represents the thermal stress coefficient, ΔT(t)-Tref represents the temperature change difference at each time point t, and the thermal stress is expressed by calculating (1-λ)*(ΔT(t)-Tref)*ce. To represent the dynamic stress of the potential risk pipeline under the vibration acceleration generated during the current operation.

[0165] S503. Determine the theoretical stress amplitude according to the difference between the maximum value and the minimum value of the theoretical comprehensive stress.

[0166] The theoretical stress amplitude is used to indicate the range of stress variation of potential risk pipelines under cyclic loading.

[0167] As can be seen from the formula for generating the theoretical comprehensive stress in step S502, one time point t corresponds to one theoretical comprehensive stress. Therefore, statistics are collected for each theoretical comprehensive stress, and the maximum and minimum values are screened out. The difference between the maximum and minimum values is then calculated and set as the theoretical stress amplitude.

[0168] For example, assuming that the time period occupied by the pipeline operation status data is t1-t2, the theoretical stress amplitude is a fixed value. In this case, the theoretical stress amplitude is set by statistically calculating the difference between the maximum and minimum values of the theoretical comprehensive stress corresponding to all time points t1-t2.

[0169] Exemplarily, the theoretical stress amplitude has different values at different time points t. For example, at t1, the theoretical stress amplitude is a pre-stored base value. At t1.1, there are two time points, t1 and t1.1. At this time, the theoretical stress amplitude is the difference between the theoretical combined stresses corresponding to t1.1 and t1. At t1.3, there are three time points, t1, t1.1, and t1.3. At this time, the theoretical stress amplitude is the difference between the maximum and minimum values of the theoretical combined stresses corresponding to t1, t1.1, and t1.3, and so on. The second calculation method can better reflect the theoretical stress amplitudes corresponding to different time points.

[0170] S504: Determine the maintenance stress concentration factor based on the post-maintenance status data.

[0171] The maintenance stress concentration factor satisfies the following formula:

[0172]

[0173] Among them, K(t) is the maintenance stress concentration coefficient corresponding to time point t, Kt0 is the preset basic stress coefficient, β1 is the first proportional coefficient, h is the real-time bulge height of the maintenance weld of the potential risk pipeline, r is the transition fillet radius of the maintenance notch of the potential risk pipeline, β2 is the second proportional coefficient, Tcr(t) is the wear depth of the potential risk pipeline at time point t, Tcr0 is the preset initial wall thickness of the potential risk pipeline, β3 is the third proportional coefficient, p(t) is the internal pressure of the potential risk pipeline at time point t, p ms is the preset standard reference pressure, p ex (t) is the change in external environmental pressure of the potential risk pipeline at time point t.

[0174] Optionally, the maintenance stress concentration factor is data used to evaluate the local stress concentration condition of the pipeline in real time.

[0175] Optionally, the base stress coefficient Kt0 can be pre-set, representing the stress concentration of the potentially risky pipeline based on its original shape. The real-time raised height h of the repair weld of the potentially risky pipeline and the transition radius r of the repair notch of the potentially risky pipeline are both manually measured in real time to assess the corrosion status of the repaired pipeline. The first, second, and third proportional coefficients β1, β2, and β3 are all pre-set.

[0176] From the above formula, we can know that when calculating the maintenance stress concentration factor, by calculating To represent the stress concentration caused by the maintenance of the weld, The larger the value of , the more obvious the geometric discontinuity and the greater the stress concentration factor. To express the stress concentration caused by corrosion and wear thickness changes, if the corrosion deepens, the pipeline resistance will weaken and the stress concentration coefficient will increase. To represent the stress fluctuation caused by internal / external pressure fluctuations. If the pressure fluctuations are frequent and large in amplitude, they will have an exponentially amplifying effect on the stress concentration factor.

[0177] The current pipeline fatigue damage value satisfies the following formula:

[0178]

[0179] Where CPF is the current pipeline fatigue damage value, N is the total number of categories of preset stress amplitude, Nj is the number of pressure load cycles under the j-th preset stress amplitude, NAj is the theoretical number of load cycles under the j-th preset stress amplitude, K(t) is the maintenance stress concentration factor corresponding to time point t, A fst is the theoretical stress amplitude.

[0180] Optionally, the theoretical number of load cycles is pre-set via a fatigue design curve.

[0181] Understandably, a potentially hazardous pipeline experiences a variety of stress amplitude cycles during operation. To accurately predict the current pipeline fatigue damage, these complex stress cycles must be broken down into several categories with varying stress amplitudes, one for each category, for a total of N categories. This is then combined with the theoretical stress amplitude and the maintenance stress concentration factor to accurately predict the current pipeline fatigue damage.

[0182] In some embodiments, combined Figure 3 ,like Figure 6 As shown, in the above S302, the subsidiary associated coupling facilities are the pipeline segments to be detected that are obtained within the preset monitoring range with the potential risk pipeline as the center. When the current pipeline fatigue damage value is less than the pipeline fatigue damage threshold, the subsidiary associated coupling facilities of the potential risk pipeline are determined, including:

[0183] S601: Obtaining a coupled vibration feedback result of a potential risk pipeline after applying a preset test excitation to the pipeline section to be tested.

[0184] The coupled vibration feedback result is obtained through the pipeline section to be detected corresponding to the coupled vibration feedback result.

[0185] Specifically, first, a preset test excitation is applied to the pipeline section to be inspected, and then, after the preset test excitation is applied to the pipeline section to be inspected, coupled vibration feedback of the potential risk pipeline is obtained.

[0186] Optionally, the preset test excitation is a preset vibration excitation, that is, vibration is applied to the pipeline section to be tested.

[0187] Alternatively, the coupled vibration feedback may be vibration detected at the potential risk pipe.

[0188] Optionally, the preset monitoring range is a monitoring range formed by radiating outward by a preset distance from the potential risk pipeline as the core.

[0189] Optionally, the pipeline section to be inspected may be obtained by marking the pipeline according to valve and cross-connection areas within a preset monitoring range.

[0190] S602: Determine the pipeline section to be detected corresponding to the coupling vibration feedback result that is greater than or equal to the vibration feedback threshold as an auxiliary associated coupling facility.

[0191] It can be seen that when the coupled vibration feedback is greater than or equal to the vibration feedback threshold, the pipeline segment to be inspected corresponding to the coupled vibration feedback result can be set as an associated coupling facility. Specifically, the pipeline segment to be inspected within the preset monitoring range of the potential risk pipeline is first obtained. After applying a preset test excitation to the pipeline segment to be inspected, the coupled vibration feedback of the potential risk pipeline is obtained. Finally, the pipeline segment to be inspected corresponding to the coupled vibration feedback greater than or equal to the vibration feedback threshold is set as an associated coupling facility.

[0192] In some embodiments, the coupled pipeline operation data includes pressure fluctuation data and flow fluctuation data. The pressure fluctuation data includes the vibration acceleration and vibration frequency of the associated coupled facility. The flow fluctuation data includes the flow fluctuation amplitude. Based on the coupled pipeline operation data of the associated coupled facility, the coupled pipeline impact factor of the associated coupled facility is generated, including:

[0193] The coupling pipeline influence factor satisfies the following formula:

[0194]

[0195] Among them, CPF is the coupling pipeline influence factor, γ1 is the vibration influence coefficient, Ane is the vibration acceleration of the subsidiary associated coupling facility, ω is the vibration frequency of the subsidiary associated coupling facility, Fd is the vibration attenuation coefficient, Anom is the tolerance acceleration of the potential risk pipeline, γ2 is the flow influence coefficient, Qne is the flow fluctuation amplitude of the subsidiary associated coupling facility, Fv is the flow transfer attenuation coefficient, and Qnom is the standard flow fluctuation amplitude of the potential risk pipeline.

[0196] Optionally, the vibration influence coefficient γ1 and the flow influence coefficient γ2 in the above formula may be preset, and are used to represent the influence ratios of vibration and flow, respectively.

[0197] The standard flow fluctuation amplitude Qnom of the potential risk pipeline and the tolerable acceleration Anom of the potential risk pipeline can be set through pre-testing or based on the historical experience of the pipeline maintenance manager.

[0198] It can be seen from the above formula that the coupling pipeline influence factor is generated by the vibration acceleration Ane of the auxiliary associated coupling facility, the vibration frequency ω of the auxiliary associated coupling facility, and the flow fluctuation amplitude Qne of the auxiliary associated coupling facility, so as to facilitate further judgment of facility abnormality warning.

[0199] It can be seen that, first, by obtaining the coupled pipeline operation data of the subsidiary associated coupling facilities, the pressure fluctuation data and flow fluctuation data are extracted according to the coupled pipeline operation data, and then the coupled pipeline impact factor is generated according to the pressure fluctuation data and the flow fluctuation data, thereby realizing the generation of the coupled pipeline impact factor by integrating the pressure and flow transfer relationship of the subsidiary associated coupling facilities.

[0200] In some embodiments, combined Figure 3 ,like Figure 7 As shown in the figure, the operation status monitoring results of the long-distance pipeline are determined based on the coupling pipeline influencing factors, including:

[0201] S701: When the coupling pipeline impact factor is greater than or equal to the coupling pipeline impact threshold, determine that the long-distance pipeline operation status monitoring result is that there is a pipeline coupling facility abnormality, and generate a pipeline coupling facility abnormality warning, so as to perform maintenance according to the pipeline coupling facility abnormality warning.

[0202] It can be seen that when the coupling pipeline impact factor is greater than or equal to the coupling pipeline impact threshold, the operation status monitoring result of the long-distance pipeline is determined to be that there is an abnormality in the pipeline coupling facility, and a pipeline coupling facility abnormality warning is generated, so that maintenance can be carried out according to the pipeline coupling facility abnormality warning, thereby solving the problem of incomplete pipeline operation monitoring and low pipeline operation monitoring accuracy caused by only monitoring the pipeline itself and ignoring other facilities that interact with the pipeline and have an impact on the pipeline operation in the prior art.

[0203] S702: When the coupling pipeline impact factor is less than the coupling pipeline impact threshold, determine a risk pipeline operation safety instruction, and continuously monitor the long-distance pipeline according to the risk pipeline operation safety instruction.

[0204] It's understood that when the coupling pipeline impact factor is less than the coupling pipeline impact threshold, it indicates that there are no issues with the potential risk pipeline and its associated coupling facilities. Therefore, a risk pipeline operation safety instruction is generated, and the long-distance pipeline is continuously monitored according to the risk pipeline operation safety instruction. This continuous monitoring includes, but is not limited to, patrol inspections, electromagnetic testing, and ultrasonic testing to better monitor the long-distance pipeline.

[0205] In some embodiments, a method for monitoring the operating status of a long-distance pipeline further includes:

[0206] When the current pipeline fatigue damage value is greater than or equal to the pipeline fatigue damage threshold, a risk pipeline status abnormality warning is generated, so that maintenance can be carried out according to the risk pipeline status abnormality warning.

[0207] For example, if the current pipeline fatigue damage value is greater than or equal to the pipeline fatigue damage threshold, a risk pipeline status abnormality warning is generated, and then the risk pipeline status abnormality warning can be sent to the long-distance pipeline maintenance personnel, and the long-distance pipeline maintenance personnel can be instructed to repair the long-distance pipeline.

[0208] As can be seen, in order to provide timely warnings for potential risk pipelines, the embodiments of the present application generate a risk pipeline abnormality warning when the current pipeline fatigue damage is greater than or equal to the pipeline fatigue damage threshold, and send the risk pipeline abnormality warning to long-distance pipeline maintenance personnel, instructing them to repair the long-distance pipeline. When the risk pipeline abnormality warning is sent to the long-distance pipeline maintenance personnel, the current pipeline fatigue damage is also sent to the long-distance pipeline maintenance personnel, so that the long-distance pipeline maintenance personnel can understand the actual situation of the potential risk pipeline and then perform further maintenance based on the actual pipeline damage.

[0209] The above mainly introduces the solution provided by the embodiment of the present application from the perspective of method. In order to realize the above functions, it includes hardware structures and / or software modules corresponding to the execution of each function. Those skilled in the art should easily appreciate that, in combination with the units and algorithm steps of each example described in the embodiments disclosed herein, the present application can be implemented in the form of hardware or a combination of hardware and computer software. Whether a function is executed in a hardware or computer software driven hardware manner depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of this application.

[0210] In the embodiments of the present application, the functional modules of the long-distance pipeline operation status monitoring device can be divided according to the above-mentioned method examples. For example, each functional module can be divided according to each function, or two or more functions can be integrated into a single processing module. The above-mentioned integrated modules can be implemented in the form of hardware or software functional modules. Optionally, the module division in the embodiments of the present application is illustrative and is only a logical functional division. In actual implementation, other division methods may be used.

[0211] Figure 8 FIG. 1 shows a schematic diagram of a long-distance pipeline operation status monitoring device provided in an embodiment of the present application. Figure 8 As shown, the long-distance pipeline operation status monitoring device includes: a communication unit 801 and a processing unit 802.

[0212] The communication unit 801 is used to determine a potential risk pipeline in a long-distance pipeline and generate a current pipeline fatigue damage value of the potential risk pipeline based on the pipeline operation status data of the potential risk pipeline.

[0213] Processing unit 802 is configured to determine, when the current pipeline fatigue damage value is less than the pipeline fatigue damage threshold, the associated coupling facilities of the potential risk pipeline; the associated coupling facilities are pipeline segments to be detected that are obtained within a preset monitoring range centered on the potential risk pipeline.

[0214] The processing unit 802 is further configured to generate a coupling pipeline impact factor of the subsidiary-associated coupling facility based on the coupling pipeline operation data of the subsidiary-associated coupling facility; the coupling pipeline impact factor is used to indicate whether the subsidiary-associated coupling facility is abnormal.

[0215] The processing unit 802 is further configured to determine the operation status monitoring result of the long-distance pipeline according to the coupling pipeline influencing factor.

[0216] Optionally, the processing unit 802 is specifically configured to:

[0217] The historical pipeline operation data of pre-marked risk pipelines in the long-distance pipeline is obtained; the pre-marked risk pipelines are pre-set pipelines; and the long-distance pipeline includes multiple pre-marked risk pipelines.

[0218] The pipeline operation usage intensity value of the pre-marked risk pipeline is calculated based on the preset unit operation time and the historical pipeline operation data of the pre-marked risk pipeline; the pipeline operation usage intensity value is determined based on the unit operation time corresponding to the pipeline operation usage intensity value.

[0219] The pipeline operation intensity value within the pre-marked intensity range is determined to obtain the risk-marked intensity value. The pre-marked intensity is a pre-set intensity value for when the operation load of the pre-marked risk pipeline is large.

[0220] According to the risk mark usage intensity value, determine the pipeline usage fluctuation intensity value corresponding to the risk mark usage intensity value. The pipeline usage fluctuation intensity value satisfies the following formula:

[0221]

[0222] Among them, IF is the pipeline usage fluctuation intensity value, n1 is the number of risk mark usage intensity values, n2 is the total number of pipeline operation usage intensity values, Sui is the i-th risk mark usage intensity value, and ΔSus is the mean of the risk mark usage intensity values.

[0223] The pre-marked risk pipeline corresponding to the pipeline usage fluctuation intensity value greater than or equal to the usage intensity threshold is determined as a potential risk pipeline.

[0224] Optionally, the pipeline operation intensity value satisfies the following formula:

[0225]

[0226] Among them, Su is the pipeline operation intensity value, ΔTs 2 is the variance of the temperature values of each data sampling point outside the pre-marked risk pipeline within the unit operating time, p is the mean value of the pipeline pressure corresponding to each data sampling point inside the pre-marked risk pipeline within the unit operating time, D is the inner diameter of the pre-marked risk pipeline, k2 is the service loss coefficient of the pre-marked risk pipeline, k1 is the material compressive strength coefficient of the pre-marked risk pipeline, din is the thickness of the pre-marked risk pipeline, L is the length of the pre-marked risk pipeline, and a v is the average vibration acceleration of each data sampling point outside the pre-marked risk pipeline within the unit operating time, A is the pipeline cross-sectional area of the pre-marked risk pipeline, dex is the thickness of the barrier material attached to the outside of the pre-marked risk pipeline, and k3 is the barrier material coefficient of the barrier material attached to the outside of the pre-marked risk pipeline.

[0227] Optionally, the pipeline operation status data of the potential risk pipeline includes: pipeline internal pressure data, pipeline real-time vibration data, real-time temperature data and post-repair status data. The processing unit 802 is specifically configured to:

[0228] Generates the number of pressure load cycles based on the internal pressure data of the pipe.

[0229] The theoretical comprehensive stress is determined based on the real-time vibration data and real-time temperature data of the pipeline. The theoretical comprehensive stress satisfies the following formula:

[0230]

[0231] Among them, St(t) is the theoretical comprehensive stress at time point t, λ is the reference stress weight coefficient, ΔT(t) is the temperature of the potential risk pipeline at time point t, Tref is the preset pipeline reference temperature, ce is the thermal expansion coefficient of the potential risk pipeline, ρ is the density of the potential risk pipeline, a(t) is the vibration acceleration of the potential risk pipeline at time point t, and St is the pipeline hardness coefficient of the potential risk pipeline.

[0232] The theoretical stress amplitude is determined based on the difference between the maximum and minimum values in the theoretical comprehensive stress; the theoretical stress amplitude is used to represent the range of stress variation of potential risk pipelines under cyclic loads.

[0233] According to the post-maintenance status data, the maintenance stress concentration factor is determined, and the maintenance stress concentration factor satisfies the following formula:

[0234]

[0235] Among them, K(t) is the maintenance stress concentration coefficient corresponding to time point t, Kt0 is the preset basic stress coefficient, β1 is the first proportional coefficient, h is the real-time bulge height of the maintenance weld of the potential risk pipeline, r is the transition fillet radius of the maintenance notch of the potential risk pipeline, β2 is the second proportional coefficient, Tcr(t) is the wear depth of the potential risk pipeline at time point t, Tcr0 is the preset initial wall thickness of the potential risk pipeline, β3 is the third proportional coefficient, p(t) is the internal pressure of the potential risk pipeline at time point t, p ms is the preset standard reference pressure, p ex (t) is the change in external environmental pressure of the potential risk pipeline at time point t.

[0236] The current pipeline fatigue damage value satisfies the following formula:

[0237]

[0238] Where CPF is the current pipeline fatigue damage value, N is the total number of categories of preset stress amplitude, Nj is the number of pressure load cycles under the j-th preset stress amplitude, NAj is the theoretical number of load cycles under the j-th preset stress amplitude, K(t) is the maintenance stress concentration factor corresponding to time point t, A fst is the theoretical stress amplitude.

[0239] Optionally, the auxiliary associated coupling facility is a pipeline segment to be detected that is obtained within a preset monitoring range with the potential risk pipeline as the center; the processing unit 802 is specifically configured to:

[0240] After applying a preset test excitation to the pipeline section to be inspected, the coupled vibration feedback result of the potential risk pipeline is obtained; the coupled vibration feedback result is obtained through the pipeline section to be inspected corresponding to the coupled vibration feedback result.

[0241] The pipeline section to be detected corresponding to the coupling vibration feedback result greater than or equal to the vibration feedback threshold is determined as the auxiliary associated coupling facility.

[0242] Optionally, the coupled pipeline operation data includes: pressure fluctuation data and flow fluctuation data; the pressure fluctuation data includes the vibration acceleration and vibration frequency of the associated coupled facilities; the flow fluctuation data includes the flow fluctuation amplitude. The processing unit 802 is specifically configured to:

[0243] The coupling pipeline influence factor satisfies the following formula:

[0244]

[0245] Among them, CPF is the coupling pipeline influence factor, γ1 is the vibration influence coefficient, Ane is the vibration acceleration of the subsidiary associated coupling facility, ω is the vibration frequency of the subsidiary associated coupling facility, Fd is the vibration attenuation coefficient, Anom is the tolerance acceleration of the potential risk pipeline, γ2 is the flow influence coefficient, Qne is the flow fluctuation amplitude of the subsidiary associated coupling facility, Fv is the flow transfer attenuation coefficient, and Qnom is the standard flow fluctuation amplitude of the potential risk pipeline.

[0246] Optionally, the processing unit 802 is specifically configured to:

[0247] When the coupling pipeline impact factor is greater than or equal to the coupling pipeline impact threshold, the operation status monitoring result of the long-distance pipeline is determined to be an abnormality of the pipeline coupling facility, and a pipeline coupling facility abnormality warning is generated, so that maintenance can be carried out according to the pipeline coupling facility abnormality warning.

[0248] When the coupling pipeline impact factor is less than the coupling pipeline impact threshold, the risk pipeline operation safety instructions are determined, and the long-distance pipeline is continuously monitored according to the risk pipeline operation safety instructions.

[0249] Optionally, the processing unit 802 is further configured to:

[0250] When the current pipeline fatigue damage value is greater than or equal to the pipeline fatigue damage threshold, a risk pipeline status abnormality warning is generated, so that maintenance can be carried out according to the risk pipeline status abnormality warning.

[0251] An embodiment of the present application further provides a computer-readable storage medium, which includes computer-executable instructions. When the computer-executable instructions are executed on a computer, the computer executes the long-distance pipeline operation status monitoring method provided in the above embodiment.

[0252] An embodiment of the present application also provides a computer program that can be directly loaded into a memory and contains software code. After being loaded and executed by a computer, the computer program can implement the long-distance pipeline operation status monitoring method provided in the above embodiment.

[0253] Those skilled in the art will appreciate that, in one or more of the examples above, the functions described herein can be implemented using hardware, software, firmware, or any combination thereof. When implemented using software, these functions can be stored in a computer-readable medium or transmitted as one or more instructions or codes on a computer-readable medium. Computer-readable media include computer-readable storage media and communication media, wherein communication media include any medium that facilitates the transmission of a computer program from one place to another. The storage medium can be any available medium that can be accessed by a general-purpose or special-purpose computer.

[0254] Through the description of the above implementation methods, technical personnel in the relevant field can clearly understand that for the convenience and simplicity of description, only the division of the above-mentioned functional modules is used as an example. In actual applications, the above-mentioned functions can be assigned to different functional modules as needed, that is, the internal structure of the device can be divided into different functional modules to complete all or part of the functions described above.

[0255] In the several embodiments provided in this application, it should be understood that the disclosed devices and methods can be implemented in other ways. For example, the device embodiments described above are merely schematic. For example, the division of the modules or units is merely a logical function division, and there may be other division methods in actual implementation. For example, multiple units or components can be combined or integrated into another device, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms. The units described as separate components may or may not be physically separated, and the components shown as units may be one physical unit or multiple physical units, that is, they may be located in one place, or they may be distributed in multiple different places. Some or all of the units can be selected according to actual needs to achieve the purpose of the scheme of this embodiment.

[0256] In addition, each functional unit in each embodiment of the present application can be integrated into a processing unit, or each unit can exist physically alone, or two or more units can be integrated into one unit. The above-mentioned integrated unit can be implemented in the form of hardware or in the form of a software functional unit. If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a readable storage medium. Based on this understanding, the technical solution of the embodiment of the present application is essentially or in other words, the part that contributes to the general technology or all or part of the technical solution can be embodied in the form of a software product, which is stored in a storage medium and includes several instructions for making a device (which can be a single-chip microcomputer, chip, etc.) or a processor (processor) perform all or part of the steps of the method described in each embodiment of the present application. The aforementioned storage medium includes various media that can store program code, such as a USB flash drive, a mobile hard disk, a ROM, a RAM, a magnetic disk, or an optical disk.

[0257] The above description is merely a specific embodiment of the present application, but the scope of protection of the present application is not limited thereto. Any changes or substitutions that can be easily conceived by a person skilled in the art within the technical scope disclosed in the present application should be included in the scope of protection of the present application. Therefore, the scope of protection of the present application should be based on the scope of protection of the claims.

Claims

1. A method for monitoring the operating status of a long-distance pipeline, characterized in that: include: Determine a potential risk pipeline in a long-distance pipeline, and generate a current pipeline fatigue damage value of the potential risk pipeline based on pipeline operation status data of the potential risk pipeline; When the current pipeline fatigue damage value is less than the pipeline fatigue damage threshold, determining the subsidiary associated coupling facility of the potential risk pipeline; the subsidiary associated coupling facility is a pipeline segment to be detected obtained within a preset monitoring range with the potential risk pipeline as the center; generating a coupling pipeline impact factor of the subsidiary associated coupling facility according to the coupled pipeline operation data of the subsidiary associated coupling facility; the coupled pipeline impact factor is used to indicate whether the subsidiary associated coupling facility is abnormal; An operation status monitoring result of the long-distance pipeline is determined according to the coupling pipeline influencing factor.

2. The method according to claim 1, characterized in that The identification of potential risk pipelines in long-distance pipelines includes: Acquire historical pipeline operation data of a pre-marked risk pipeline in the long-distance pipeline; the pre-marked risk pipeline is a pre-set pipeline; the long-distance pipeline includes a plurality of the pre-marked risk pipelines; Calculating a pipeline operation usage intensity value of the pre-marked risk pipeline according to a preset unit operation time and historical pipeline operation data of the pre-marked risk pipeline; the pipeline operation usage intensity value is determined according to the unit operation time corresponding to the pipeline operation usage intensity value; Determine the pipeline operation intensity value within the pre-marked intensity range to obtain a risk-marked intensity value; the pre-marked intensity is a pre-set intensity value when the operation load of the pre-marked risk pipeline is large; According to the risk mark usage intensity value, a pipeline usage fluctuation intensity value corresponding to the risk mark usage intensity value is determined, and the pipeline usage fluctuation intensity value satisfies the following formula: Wherein, IF is the pipeline usage fluctuation intensity value, n1 is the number of the risk mark usage intensity values, n2 is the total number of the pipeline operation usage intensity values, Sui is the i-th risk mark usage intensity value, and ΔSus is the mean of the risk mark usage intensity values; The pre-marked risky pipeline corresponding to the pipeline usage fluctuation intensity value that is greater than or equal to a usage intensity threshold is determined as the potential risky pipeline.

3. The method according to claim 2, characterized in that The pipeline operation intensity value satisfies the following formula: Among them, Su is the pipeline operation intensity value, ΔTs 2 is the variance of the temperature values of each data sampling point outside the pre-marked risk pipeline within the unit operating time, p is the mean value of the pipeline pressure corresponding to each data sampling point inside the pre-marked risk pipeline within the unit operating time, D is the inner diameter of the pre-marked risk pipeline, k2 is the service loss coefficient of the pre-marked risk pipeline, k1 is the material compressive strength coefficient of the pre-marked risk pipeline, din is the thickness of the pre-marked risk pipeline, L is the length of the pre-marked risk pipeline, and a v is the average vibration acceleration of each data sampling point outside the pre-marked risk pipeline within the unit operating time, A is the pipeline cross-sectional area of the pre-marked risk pipeline, dex is the thickness of the barrier material attached to the outside of the pre-marked risk pipeline, and k3 is the barrier material coefficient of the barrier material attached to the outside of the pre-marked risk pipeline.

4. The method according to claim 1, wherein The pipeline operation status data of the potential risk pipeline includes: pipeline internal pressure data, pipeline real-time vibration data, real-time temperature data and post-repair status data; Generating the current pipeline fatigue damage value of the potential risk pipeline according to the pipeline operation status data of the potential risk pipeline includes: generating a pressure load cycle number according to the internal pressure data of the pipeline; The theoretical comprehensive stress is determined based on the real-time pipeline vibration data and the real-time temperature data. The theoretical comprehensive stress satisfies the following formula: Wherein, St(t) is the theoretical comprehensive stress at time point t, λ is the reference stress weight coefficient, ΔT(t) is the temperature of the potential risk pipeline at time point t, Tref is the preset pipeline reference temperature, ce is the thermal expansion coefficient of the potential risk pipeline, ρ is the density of the potential risk pipeline, a(t) is the vibration acceleration of the potential risk pipeline at time point t, and St is the pipeline hardness coefficient of the potential risk pipeline; Determine a theoretical stress amplitude according to the difference between the maximum value and the minimum value of the theoretical comprehensive stress; the theoretical stress amplitude is used to represent the stress variation range of the potential risk pipeline under cyclic load; According to the post-maintenance state data, a maintenance stress concentration factor is determined, and the maintenance stress concentration factor satisfies the following formula: Wherein, K(t) is the maintenance stress concentration coefficient corresponding to time point t, Kt0 is the preset basic stress coefficient, β1 is the first proportional coefficient, h is the real-time bulge height of the maintenance weld of the potential risk pipeline, r is the transition fillet radius of the maintenance notch of the potential risk pipeline, β2 is the second proportional coefficient, Tcr(t) is the wear depth of the potential risk pipeline at the time point t, Tcr0 is the preset initial wall thickness of the potential risk pipeline, β3 is the third proportional coefficient, p(t) is the internal pressure of the potential risk pipeline at the time point t, p ms is the preset standard reference pressure, p ex (t) is the change in external environmental pressure of the potential risk pipeline at the time point t; The current pipeline fatigue damage value satisfies the following formula: Wherein, CPF is the current pipeline fatigue damage value, N is the total number of categories of preset stress amplitude, Nj is the number of pressure load cycles under the j-th preset stress amplitude, NAj is the theoretical number of load cycles under the j-th preset stress amplitude, K(t) is the maintenance stress concentration factor corresponding to time point t, A fst is the theoretical stress amplitude.

5. The method according to claim 1, wherein The subsidiary associated coupling facility is a pipeline segment to be detected that is obtained within a preset monitoring range with the potential risk pipeline as the center; when the current pipeline fatigue damage value is less than the pipeline fatigue damage threshold, determining the subsidiary associated coupling facility of the potential risk pipeline includes: Acquiring a coupled vibration feedback result of the potential risk pipeline after applying a preset test excitation to the pipeline section to be inspected; the coupled vibration feedback result is obtained by the pipeline section to be inspected corresponding to the coupled vibration feedback result; The pipeline section to be detected corresponding to the coupling vibration feedback result that is greater than or equal to a vibration feedback threshold is determined as the subsidiary associated coupling facility.

6. The method according to claim 1, characterized in that The coupled pipeline operation data includes: pressure fluctuation data and flow fluctuation data; the pressure fluctuation data includes the vibration acceleration and vibration frequency of the associated coupled facility; the flow fluctuation data includes the flow fluctuation amplitude; Generating the coupling pipeline impact factor of the subsidiary associated coupling facility according to the coupled pipeline operation data of the subsidiary associated coupling facility includes: The coupling pipeline influence factor satisfies the following formula: Among them, CPF is the coupling pipeline influence factor, γ1 is the vibration influence coefficient, Ane is the vibration acceleration of the subsidiary associated coupling facility, ω is the vibration frequency of the subsidiary associated coupling facility, Fd is the vibration attenuation coefficient, Anom is the tolerance acceleration of the potential risk pipeline, γ2 is the flow influence coefficient, Qne is the flow fluctuation amplitude of the subsidiary associated coupling facility, Fv is the flow transfer attenuation coefficient, and Qnom is the standard flow fluctuation amplitude of the potential risk pipeline.

7. The method according to claim 1, characterized in that Determining the operation status monitoring result of the long-distance pipeline according to the coupling pipeline influencing factor includes: When the coupling pipeline impact factor is greater than or equal to the coupling pipeline impact threshold, determining that the operation status monitoring result of the long-distance pipeline is that there is an abnormality in the pipeline coupling facility, and generating a pipeline coupling facility abnormality warning, so as to perform maintenance according to the pipeline coupling facility abnormality warning; When the coupling pipeline impact factor is less than the coupling pipeline impact threshold, a risky pipeline operation safety instruction is determined, and the long-distance pipeline is continuously monitored according to the risky pipeline operation safety instruction.

8. The method according to claim 1, characterized in that Also includes: When the current pipeline fatigue damage value is greater than or equal to the pipeline fatigue damage threshold, a risk pipeline state abnormality warning is generated, so that maintenance is performed according to the risk pipeline state abnormality warning.

9. A long-distance pipeline operation status monitoring system, characterized in that: include: A pipeline fatigue damage generation module is used to determine a potential risk pipeline in a long-distance pipeline and generate a current pipeline fatigue damage value of the potential risk pipeline based on the pipeline operation status data of the potential risk pipeline; A coupling impact factor generation module is used to determine the subsidiary associated coupling facilities of the potential risk pipeline and generate a coupling pipeline impact factor; The coupling facility warning generation module is used to generate a pipeline coupling facility abnormality warning when it is determined that the operation status monitoring result of the long-distance pipeline is that the pipeline coupling facility is abnormal, so as to perform maintenance according to the pipeline coupling facility abnormality warning.

10. A long-distance pipeline operation status monitoring device, characterized in that: include: A processor and a memory; wherein the memory is used to store one or more programs, and the one or more programs include computer-executable instructions. When the device is running, the processor executes the computer-executable instructions stored in the memory to enable the device to perform the method according to any one of claims 1 to 8.

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