A gas pipeline full life cycle analysis and monitoring method and system

Abstract

The present invention relates to the field of pipeline construction, specifically to a method, device and system for analyzing and monitoring the entire life cycle of a gas pipeline, which collects and analyzes the surface images of the gas pipeline laying area during the entire life cycle of the pipeline operation, obtains the surface morphology change data of the laying area, and determines the unstable surface sub-area; collects and analyzes the underground dynamic change discrete data of the underground space corresponding to the unstable surface sub-area, determines the soil layer change trend of the underground space, estimates the internal pressure distribution information of the soil layer in the underground space, and combines the morphological characteristic information of the gas pipeline to determine the structurally susceptible position points of the gas pipeline; performs time domain analysis on the air pressure data of the associated pipeline section of the structurally susceptible position point, and predicts the characteristic information of the pipeline failure. The present invention can realize large-scale inspection and fixed-point fault identification and prediction of the gas pipeline under the pressure effect caused by the soil layer structure change in the underground space where the gas pipeline is located, taking full account of the pressure generated by the soil layer structure change in the underground space where the gas pipeline is located.

Description

Technical Field

[0001] The present invention relates to the field of pipeline construction, and in particular to a method and system for analyzing and monitoring the entire life cycle of a gas pipeline. Background Art

[0002] Gas pipelines are an important part of urban livelihood projects. The ability of gas pipelines to maintain normal operation directly affects the reliability of gas use by residents. In order to increase the coverage of natural gas transmission and supply, the coverage area of ​​the gas pipeline network is also increased accordingly. After the gas pipeline network is laid, it is also necessary to monitor the gas pipeline network to ensure the safety of gas transmission and the stability of gas pressure.

[0003] Gas pipelines are laid in a deep underground manner, which makes the monitoring of gas pipelines have certain limitations. The existing focus of monitoring gas pipelines is to monitor whether there are pipeline leaks, usually by using ultrasonic detection to check one by one along the pipeline. The above method is not only inefficient, but also cannot monitor gas pipelines over a large area in a short period of time. At the same time, the detection effect is single, and it can only detect points where obvious gas leaks have occurred in the pipeline. It cannot detect pipeline ruptures and deformations caused by the soil structure of the underground space where the gas pipeline is located, reducing the real-time and comprehensiveness of gas pipeline monitoring. It can be seen that how to identify the trend of soil changes in the underground space of the laying area from the changes in the surface morphology of the gas pipeline laying area, and how to identify and predict faults in the entire life cycle of the gas pipeline is of great significance. Summary of the invention

[0004] In order to realize large-scale inspection and fixed-point fault identification and prediction of gas pipelines under the pressure effect caused by the change of soil structure in the underground space where the gas pipeline is located, the present invention provides a gas pipeline full life cycle analysis and monitoring method, which includes the following steps:

[0005] Collecting surface images of the gas pipeline laying area during the entire life cycle of the pipeline operation, and dynamically identifying the surface morphology change data of the laying area from the surface images; determining the unstable surface sub-area in the laying area based on the surface morphology change data;

[0006] Collecting underground dynamic change discrete data of the underground space corresponding to the unstable surface sub-region, determining the soil layer change trend of the underground space based on the underground dynamic change discrete data; estimating the internal pressure distribution information of the soil layer of the underground space based on the soil layer change trend;

[0007] Based on the internal pressure distribution information of the soil layer and the morphological characteristic information of the gas pipeline, the structurally vulnerable position points of the gas pipeline are determined; the air pressure data of the pipeline section associated with the structurally vulnerable position points are collected, and the air pressure data are subjected to a time domain analysis over the entire life cycle of the pipeline operation to predict the characteristic information of the occurrence of failures in the gas pipeline.

[0008] Preferably, the surface images of the gas pipeline laying area during the entire life cycle of the pipeline operation are collected, and the surface morphology change data of the laying area are obtained from the surface images by dynamic recognition; based on the surface morphology change data, the unstable surface sub-area in the laying area is determined, specifically:

[0009] Performing synchronous panoramic photography and meteorological detection on the surface corresponding to the gas pipeline laying area, and obtaining the surface panoramic images and meteorological data of the gas pipeline laying area during the entire life cycle of the pipeline operation;

[0010] Based on the meteorological data, determine the time information of the preset meteorological event occurring in the gas pipeline laying area; based on the time information, extract a number of surface panoramic image frames from the surface panoramic image; perform surface contour recognition and contour position change recognition on all surface panoramic image frames to obtain surface morphology change data of the laying area; wherein the surface morphology change data includes contour height change data and contour direction change data of the surface corresponding to the laying area;

[0011] The surface morphology change data is analyzed to determine the height fluctuation distribution information and the surface structure contour continuous state distribution information of the surface corresponding to the paving area; based on the height fluctuation distribution information and the surface structure contour continuous state distribution information, the unstable sub-area of ​​the surface within the paving area is determined.

[0012] Preferably, the collecting of underground dynamic change discrete data of the underground space corresponding to the unstable surface sub-area, determining the soil layer change trend of the underground space based on the underground dynamic change discrete data; estimating the internal pressure distribution information of the soil layer of the underground space based on the soil layer change trend, specifically includes:

[0013] Based on the boundary shape of the unstable surface sub-region, a number of discrete underground feature points corresponding to the underground space of the unstable surface sub-region are calibrated; based on the position information of all underground feature points, underground dynamic change discrete data corresponding to all underground feature points are collected; wherein the underground dynamic change discrete data includes the displacement rate and displacement direction corresponding to each underground feature point;

[0014] Based on the underground depth of all underground feature points, determine the soil layers to which all underground feature points belong; perform continuous fitting prediction on the underground dynamic change discrete data of all underground feature points under the same soil layer to determine the displacement vector of the soil layer; perform integrated analysis on the displacement vectors of all soil layers to determine the displacement change trend of the soil layer in the underground space;

[0015] Based on the physical characteristics of all soil layers in the underground space and the displacement change trends of the soil layers, the extrusion pressure distribution information inside each soil layer in the underground space and the extrusion pressure distribution information between any two adjacent soil layers are estimated as the internal pressure distribution information of the soil layers in the underground space.

[0016] Preferably, based on the internal pressure distribution information of the soil layer and the morphological characteristic information of the gas pipeline, the structure susceptible position point of the gas pipeline is determined; the air pressure data of the pipeline section associated with the structure susceptible position point is collected, and the time domain analysis of the air pressure data for the entire life cycle of the pipeline operation is performed to predict the fault occurrence characteristic information of the gas pipeline, specifically:

[0017] Based on the internal pressure distribution information of the soil layer, determine the abnormal point group of internal pressure action of the underground space; based on the morphological characteristic information of the extension path of the gas pipeline in the underground space, determine the structural vulnerable point group of the gas pipeline in the underground space; based on the relative position relationship between the abnormal point group of internal pressure action and the structural vulnerable point group, screen the structural vulnerable position points of the gas pipeline from the structural vulnerable point group;

[0018] The air pressure data of the pipeline section associated with the structure's susceptible location in the gas pipeline is collected, and the time domain and spatial domain change analysis of the air pressure data over the entire life cycle of the pipeline operation is performed to predict the location point where the gas leakage fault occurs and the gas leakage flow rate of the associated pipeline section, which is used as the characteristic information of the gas pipeline fault.

[0019] On the other hand, the present invention provides a gas pipeline full life cycle analysis and monitoring device, the device comprising the following modules:

[0020] A surface morphology recognition module is used to collect surface images of the gas pipeline laying area during the entire life cycle of the pipeline operation, and dynamically identify the surface morphology change data of the laying area from the surface images;

[0021] An unstable region determination module, used for determining an unstable sub-region of the surface within the paving area based on the surface topography change data;

[0022] An underground soil layer change trend determination module is used to collect underground dynamic change discrete data of the underground space corresponding to the unstable surface sub-area, and determine the soil layer change trend of the underground space based on the underground dynamic change discrete data;

[0023] A soil layer internal pressure distribution estimation module, used to estimate the soil layer internal pressure distribution information of the underground space based on the soil layer change trend;

[0024] A pipeline location point determination module, used to determine a location point of the gas pipeline that is susceptible to structural influence based on the internal pressure distribution information of the soil layer and the morphological characteristic information of the gas pipeline;

[0025] The fault occurrence prediction module is used to collect the air pressure data of the associated pipeline section of the structure's susceptible location point, perform time domain analysis on the air pressure data over the entire life cycle of the pipeline operation, and predict the fault occurrence characteristic information of the gas pipeline.

[0026] Preferably, the surface morphology recognition module is used to collect surface images of the gas pipeline laying area during the entire life cycle of the pipeline operation, and dynamically identify the surface morphology change data of the laying area from the surface images, specifically:

[0027] Performing synchronous panoramic photography and meteorological detection on the surface corresponding to the gas pipeline laying area, and obtaining the surface panoramic images and meteorological data of the gas pipeline laying area during the entire life cycle of the pipeline operation;

[0028] Based on the meteorological data, determine the time information of the preset meteorological event occurring in the gas pipeline laying area; based on the time information, extract a number of surface panoramic image frames from the surface panoramic image; perform surface contour recognition and contour position change recognition on all surface panoramic image frames to obtain surface morphology change data of the laying area; wherein the surface morphology change data includes contour height change data and contour direction change data of the surface corresponding to the laying area;

[0029] The unstable area determination module is used to determine the unstable surface sub-area in the paving area based on the surface morphology change data, specifically:

[0030] The surface morphology change data is analyzed to determine the height fluctuation distribution information and the surface structure contour continuous state distribution information of the surface corresponding to the paving area; based on the height fluctuation distribution information and the surface structure contour continuous state distribution information, the unstable sub-area of ​​the surface within the paving area is determined.

[0031] Preferably, the underground soil layer change trend determination module is used to collect the underground dynamic change discrete data of the underground space corresponding to the unstable surface sub-area, and determine the soil layer change trend of the underground space based on the underground dynamic change discrete data, specifically:

[0032] Based on the boundary shape of the unstable surface sub-region, a number of discrete underground feature points corresponding to the underground space of the unstable surface sub-region are calibrated; based on the position information of all underground feature points, underground dynamic change discrete data corresponding to all underground feature points are collected; wherein the underground dynamic change discrete data includes the displacement rate and displacement direction corresponding to each underground feature point;

[0033] Based on the underground depth of all underground feature points, determine the soil layers to which all underground feature points belong; perform continuous fitting prediction on the underground dynamic change discrete data of all underground feature points under the same soil layer to determine the displacement vector of the soil layer; perform integrated analysis on the displacement vectors of all soil layers to determine the displacement change trend of the soil layer in the underground space;

[0034] The soil layer internal pressure distribution estimation module is used to estimate the soil layer internal pressure distribution information of the underground space based on the soil layer change trend, specifically:

[0035] Based on the physical characteristics of all soil layers in the underground space and the displacement change trends of the soil layers, the extrusion pressure distribution information inside each soil layer in the underground space and the extrusion pressure distribution information between any two adjacent soil layers are estimated as the internal pressure distribution information of the soil layers in the underground space.

[0036] Preferably, the pipeline location point determination module is used to determine the structurally susceptible location point of the gas pipeline based on the internal pressure distribution information of the soil layer and the morphological characteristic information of the gas pipeline, specifically:

[0037] Based on the internal pressure distribution information of the soil layer, the abnormal point group of internal pressure action in the underground space is determined; based on the morphological characteristic information of the extension path of the gas pipeline in the underground space, the structural vulnerable point group of the gas pipeline in the underground space is determined; based on the relative position relationship between the abnormal point group of internal pressure action and the structural vulnerable point group, the structurally susceptible position points of the gas pipeline are screened from the structural vulnerable point group.

[0038] Preferably, the fault occurrence prediction module is used to collect the gas pressure data of the associated pipeline section of the susceptible location point of the structure, perform time domain analysis on the gas pressure data for the entire life cycle of the pipeline operation, and predict the fault occurrence characteristic information of the gas pipeline, specifically:

[0039] The air pressure data of the pipeline section associated with the structure's susceptible location in the gas pipeline is collected, and the time domain and spatial domain change analysis of the air pressure data over the entire life cycle of the pipeline operation is performed to predict the location point where the gas leakage fault occurs and the gas leakage flow rate of the associated pipeline section, which is used as the characteristic information of the gas pipeline fault.

[0040] In addition, the present invention also provides a gas pipeline full life cycle analysis and monitoring system, the system comprising:

[0041] The above-mentioned gas pipeline full life cycle analysis and monitoring device;

[0042] The early warning notification device is used to send an early warning notification message to the backend according to the fault occurrence characteristic information predicted by the gas pipeline full life cycle analysis and monitoring device.

[0043] Compared with the prior art, the present invention has the following beneficial effects:

[0044] Collect surface images of the gas pipeline laying area during the entire life cycle of the pipeline operation, and obtain the surface morphology change data of the laying area from the surface images; based on the surface morphology change data, determine the unstable surface sub-areas in the laying area. Gas pipelines are usually laid deep underground, making it impossible to detect the actual situation of the gas pipeline by direct visual recognition. The geological structure of the soil layer in the underground space where the gas pipeline is located will affect the safety of the pipeline structure. If there is a landslide or settlement in the underground space, the geological structure of the soil layer in the underground space will deform, causing the soil layer in a certain area to be squeezed in a specific direction. This squeezing will be transmitted to the adjacent gas pipelines. The gas pipeline will be deformed or even ruptured if it is subjected to high-intensity squeezing for a long time, resulting in the gas pipeline being unable to transport natural gas normally and stably. When a landslide or subsidence occurs in the underground space, the surface area corresponding to the underground space will sink accordingly, and the degree of subsidence is correlated to the degree of the landslide or subsidence in the underground space. Therefore, by detecting the changes in the morphology of the surface area, it is possible to determine whether there is a landslide or subsidence in the underground space below the surface area, thereby effectively overcoming the limitation that the gas pipeline cannot be directly detected because it is laid in the underground space. In addition, the structural state of the surface area will also affect the geological structural state of the underground space. For example, the surface area is washed away by heavy rain, causing the soil in the surface area to become loose, and the rainwater continuously penetrates into the underground space, increasing the soil moisture content in the underground space, making the underground space more prone to landslide or subsidence. It can be seen that there will be some key sub-areas in the entire gas pipeline laying area, and the gas pipelines located in these key sub-areas are more likely to be affected by the geological structure of the soil layer and cause failure and damage. In order to perform global detection of the gas pipeline laying area and accurately screen the location areas where the gas pipeline is prone to failure and damage, the surface morphology changes in the gas pipeline laying area can be detected first to identify the unstable surface sub-areas, and then the underground space corresponding to the unstable surface sub-areas can be dynamically identified to determine the factors affecting the safety of the gas pipeline structure. Specifically, the global surface of the gas pipeline laying area can be visually identified throughout the life cycle of the pipeline operation to obtain surface morphology change data, which fully reflects the changes in the surface morphology corresponding to the gas pipeline laying area during the entire life cycle, thereby accurately locating the unstable surface sub-areas in the laying area and limiting the scope for subsequent dynamic change detection of underground soil layers.

[0045] Collect the underground dynamic change discrete data of the underground space corresponding to the unstable surface sub-area, determine the soil layer change trend of the underground space based on the underground dynamic change discrete data; estimate the internal pressure distribution information of the soil layer of the underground space based on the soil layer change trend. According to the stable structural correlation between the underground space and the surface space in the gas pipeline laying area, by detecting the morphological unstable sub-area of ​​the surface space corresponding to the gas pipeline laying area, the area with large soil layer structure change in the underground space corresponding to the gas pipeline laying area can be mapped and determined. When the soil layer structure of the underground space is displaced, and the displacement amplitude is large and / or the displacement direction is distorted, it may cause the soil layer structure to break and fragment, thereby forming an extrusion effect distributed in a specific direction inside the soil layer. These extrusion effects will be transmitted to the gas pipeline, and are particularly obvious to the gas pipeline that is close to the soil layer structure where the fracture occurs. When the extrusion effect on the gas pipeline exceeds the pressure threshold that the pipeline can withstand or the extrusion effect is applied to the fixed position of the gas pipeline for a long time, the gas pipeline will be deformed and ruptured, affecting the normal and stable transmission of natural gas inside the gas pipeline. However, the underground space corresponding to the unstable sub-region of the surface morphology is vast. If the underground space is directly subjected to global dynamic detection, not only will a large amount of dynamic data be generated, which will increase the cost of dynamic data processing, but these dynamic data will also fail to effectively characterize the real dynamic changes of the underground space. In order to reduce the workload of dynamic data detection and analysis in the underground space and ensure the accuracy of soil layer change identification, the underground dynamic change discrete data corresponding to the unstable sub-region of the surface is collected, and the soil layer change trend of the underground space is fitted to estimate the internal pressure distribution information of the soil layer in the underground space. On the basis of using less dynamic data, the internal pressure of the underground space caused by soil layer displacement or distortion is comprehensively and quantitatively characterized, which provides sufficient and reliable basis for the subsequent identification of the location points where the gas pipeline is deformed due to pressure.

[0046] Based on the pressure distribution information inside the soil layer and the morphological characteristics of the gas pipeline, the structural vulnerable points of the gas pipeline are determined; the air pressure data of the associated pipeline section of the structural vulnerable points are collected, and the air pressure data is analyzed in the time domain for the entire life cycle of the pipeline operation to predict the fault occurrence characteristic information of the gas pipeline. The squeezing effect inside the soil layer will be transmitted to the gas pipeline. Considering the structural differences of the gas pipeline in the entire extension path, that is, the structural strength of the gas pipeline is greater in some parts and smaller in other parts, the gas pipeline has different anti-squeezing performance in different parts. For example, in the parts with more bending structures of the gas pipeline, its structural strength is smaller, and the corresponding anti-squeezing performance is also poor, that is, these parts belong to the structurally fragile parts of the gas pipeline, while in the straight extension parts of the gas pipeline, its structural strength is greater, and the corresponding anti-squeezing performance is also better. In addition, the transmission distance and application area of ​​the squeezing effect inside the soil layer to the gas pipeline will also affect the probability of deformation failure of the gas pipeline. Generally speaking, the smaller the transmission distance of the extrusion effect to a certain range on the gas pipeline and / or the larger the application area of ​​the extrusion effect on a certain range on the gas pipeline, the higher the probability of deformation failure in a certain range on the gas pipeline, that is, a certain range on the gas pipeline belongs to the range that is susceptible to the extrusion effect, and these ranges are more likely to have deformation failures than other ranges. At this time, the air pressure data of the associated pipeline sections of these ranges in the gas pipeline are collected and analyzed, and the location point of the gas leakage failure and the gas leakage flow rate of the associated pipeline section are predicted, so as to realize the identification and prediction of fixed-point faults in the gas pipeline. BRIEF DESCRIPTION OF THE DRAWINGS

[0047] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for describing the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work. Among them:

[0048] Figure 1 It is a flow chart of a gas pipeline full life cycle analysis and monitoring method provided by the present invention.

[0049] Figure 2 It is a structural diagram of a gas pipeline full life cycle analysis and monitoring device provided by the present invention.

[0050] Figure 3 It is a structural diagram of a gas pipeline full life cycle analysis and monitoring system provided by the present invention. DETAILED DESCRIPTION

[0051] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, the specific implementation methods of the present invention are described in detail below in conjunction with the accompanying drawings. It is understood that the specific embodiments described herein are only used to explain the present invention, rather than to limit the present invention. It should also be noted that, for ease of description, only the parts related to the present invention rather than all structures are shown in the accompanying drawings. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention.

[0052] The terms "including" and "having" and any variations thereof in the present invention are intended to cover non-exclusive inclusions. For example, a process, method, system, product or device comprising a series of steps or units is not limited to the listed steps or units, but may optionally include steps or units not listed, or may optionally include other steps or units inherent to these processes, methods, products or devices.

[0053] Reference to "embodiments" herein means that a particular feature, structure, or characteristic described in conjunction with the embodiments may be included in at least one embodiment of the present invention. The appearance of the phrase in various places in the specification does not necessarily refer to the same embodiment, nor is it an independent or alternative embodiment that is mutually exclusive with other embodiments. It is explicitly and implicitly understood by those skilled in the art that the embodiments described herein may be combined with other embodiments.

[0054] See also Figure 1 As shown, the present invention provides a gas pipeline full life cycle analysis and monitoring method, the method comprising the following steps:

[0055] S100, collecting surface images of the gas pipeline laying area during the entire life cycle of the pipeline operation, and obtaining surface morphology change data of the laying area from the surface images; based on the surface morphology change data, determining the unstable surface sub-area in the laying area.

[0056] Furthermore, the surface images of the gas pipeline laying area during the entire life cycle of the pipeline operation are collected, and the surface morphology change data of the laying area are obtained from the surface images through dynamic recognition; based on the surface morphology change data, the unstable surface sub-areas in the laying area are determined, specifically:

[0057] Synchronous panoramic photography and meteorological detection are carried out on the surface of the gas pipeline laying area, so as to obtain panoramic images and meteorological data of the surface of the gas pipeline laying area during the entire life cycle of the pipeline operation;

[0058] Based on meteorological data, determine the time information of preset meteorological events in the gas pipeline laying area; based on the time information, extract a number of surface panoramic image frames from the surface panoramic image; perform surface contour recognition and contour position change recognition on all surface panoramic image frames to obtain surface morphology change data of the laying area; wherein the surface morphology change data includes contour height change data and contour direction change data of the surface corresponding to the laying area;

[0059] The surface morphology change data is analyzed to determine the height fluctuation distribution information and the surface structure contour continuous state distribution information of the surface corresponding to the paving area; based on the height fluctuation distribution information and the surface structure contour continuous state distribution information, the unstable surface sub-area within the paving area is determined.

[0060] Gas pipelines are laid underground in a deep buried manner. The geological structure of the soil layer in the underground space where the gas pipeline is located will affect the safety of the pipeline structure. If there is a landslide or subsidence in the underground space, the geological structure of the soil layer in the underground space will be deformed, causing the soil layer in a certain area to be squeezed in a specific direction. This squeezing will be transmitted to the adjacent gas pipelines. The gas pipeline will be deformed or even ruptured due to long-term high-intensity squeezing, resulting in the gas pipeline being unable to transport natural gas normally and stably. When the underground space collapses or subsides, the surface area corresponding to the underground space will sink accordingly, and the degree of subsidence is related to the collapse or subsidence of the underground space. Therefore, by detecting the changes in the morphology of the surface area, it is possible to determine whether there is a landslide or subsidence in the underground space below the surface area, thereby effectively overcoming the limitation that the gas pipeline cannot be directly detected because it is laid in the underground space. In addition, the structural state of the surface area will also affect the geological structural state of the underground space. For example, the surface area is washed by heavy rain, which makes the soil in the surface area loose. In addition, rainwater continues to penetrate into the underground space, increasing the soil moisture content of the underground space, making the underground space more prone to landslides or settlement. It can be seen that there will be some key sub-areas in the entire gas pipeline laying area. The gas pipelines located in these key sub-areas are more likely to be affected by the geological structure of the soil layer and cause failure and damage. Due to the laying mode of gas pipelines buried deep underground, it is impossible to perform global visual inspection of all gas pipelines in the underground space, nor is it possible to perform global inspection of the geological structure of the soil layer in the underground space. The surface area of ​​the gas pipeline laying area can be visually identified first, which provides a basis for the subsequent limitation of the dynamic data collection scope of the underground space where the gas pipeline is laid.

[0061] In order to perform global detection of the gas pipeline laying area and accurately screen the location areas where the gas pipeline is prone to failure and damage, the surface morphology changes in the gas pipeline laying area can be detected first to identify the unstable surface sub-areas, and then the underground space corresponding to the unstable surface sub-areas can be dynamically identified to determine the factors affecting the safety of the gas pipeline structure. Through the above analysis, it can be seen that the meteorological conditions such as rainfall on the surface corresponding to the gas pipeline laying area will have an adverse effect on the surface morphology, and then affect the stability of the soil structure of the corresponding underground space. In order to quickly and accurately locate the surface range that is most likely to affect the stability of the soil structure of the underground space during the panoramic visual recognition of the surface, the surface corresponding to the gas pipeline laying area is first synchronously photographed and meteorologically detected to obtain the surface panoramic image and meteorological data of the gas pipeline laying area during the entire life cycle of the pipeline operation; wherein, the entire life cycle of the pipeline operation can be but not limited to a complete operation cycle of the gas pipeline (such as a week, a month or a quarter, etc.), and the meteorological data can be but not limited to rainfall change data. The rainfall change data is analyzed to determine the duration of a preset meteorological event in which the actual rainfall in the gas pipeline laying area exceeds a preset rainfall threshold. Based on the duration of the occurrence, image frames of the surface panoramic image are extracted to obtain a number of surface panoramic image frames corresponding to the duration of the occurrence. Surface contour recognition and contour position change recognition are performed on each surface panoramic image frame to obtain contour height change data and contour direction change data (i.e., contour inclination angle data) of the surface corresponding to the laying area.

[0062] The surface contour height change data and contour direction change data are also analyzed to obtain the surface contour height fluctuation drop change distribution information and the surface structure contour oblique angle change distribution information; if the contour height fluctuation drop change distribution information indicates that the contour height drop within a unit distance of a sub-area in the surface exceeds a preset drop threshold and / or the surface structure contour oblique angle change distribution information indicates that the contour inclination angle fluctuation range of a sub-area in the surface exceeds a preset range threshold, then the corresponding sub-area is determined as an unstable surface sub-area, that is, the corresponding sub-area is very likely to sink, so as to limit the range for subsequent detection of dynamic changes in underground soil layers.

[0063] S200, collecting underground dynamic change discrete data of the underground space corresponding to the unstable sub-area on the surface, determining the soil layer change trend of the underground space based on the underground dynamic change discrete data; estimating the internal pressure distribution information of the soil layer in the underground space based on the soil layer change trend.

[0064] Furthermore, the underground dynamic change discrete data of the underground space corresponding to the unstable sub-area on the surface is collected, and the soil layer change trend of the underground space is determined based on the underground dynamic change discrete data; based on the soil layer change trend, the internal pressure distribution information of the soil layer in the underground space is estimated, specifically:

[0065] Based on the boundary shape of the unstable surface sub-region, a number of discrete underground feature points corresponding to the underground space of the unstable surface sub-region are calibrated; based on the position information of all underground feature points, underground dynamic change discrete data corresponding to all underground feature points are collected; wherein the underground dynamic change discrete data includes the displacement rate and displacement direction corresponding to each underground feature point;

[0066] Based on the underground depth of all underground feature points, determine the soil layers to which all underground feature points belong; perform continuous fitting prediction on the discrete data of underground dynamic changes of all underground feature points under the same soil layer to determine the displacement vector of the soil layer; perform integrated analysis on the displacement vectors of all soil layers to determine the displacement change trend of the soil layers in the underground space;

[0067] Based on the physical characteristics of all soil layers in the underground space and the displacement change trends of the soil layers, the extrusion pressure distribution information inside each soil layer in the underground space and the extrusion pressure distribution information between any two adjacent soil layers are estimated as the internal pressure distribution information of the soil layers in the underground space.

[0068] According to the stable structural correlation between the underground space and the surface space in the gas pipeline laying area, by detecting the unstable sub-area of ​​the surface space corresponding to the gas pipeline laying area, the area of ​​the underground space corresponding to the gas pipeline laying area with large soil structure changes can be mapped and determined. When the soil structure of the underground space is displaced, and the displacement amplitude is large and / or the displacement direction is distorted, it may cause the soil structure to break and fragment, thereby forming an extrusion effect distributed along a specific direction inside the soil layer. These extrusion effects will be transmitted to the gas pipeline, and are particularly obvious to the gas pipeline that is close to the soil structure where the fracture and fragmentation occurs. When the extrusion effect on the gas pipeline exceeds the pressure threshold that the pipeline can withstand or the extrusion effect is applied to the fixed position of the gas pipeline for a long time, the gas pipeline will be deformed and ruptured, affecting the normal and stable transmission of natural gas inside the gas pipeline. However, the underground space corresponding to the unstable sub-area of ​​the surface morphology is large. If the underground space is directly subjected to global dynamic detection, not only a large amount of dynamic data will be generated, the dynamic data processing cost will be increased, and these dynamic data cannot effectively and directionally represent the real dynamic changes of the underground space. In order to reduce the workload of underground space dynamic data detection and analysis and ensure the accuracy of soil layer change identification, discrete data of underground dynamic changes in the unstable sub-area of ​​the surface corresponding to the underground space are collected, and the soil layer change trend of the underground space is fitted to estimate the internal pressure distribution information of the soil layer in the underground space. On the basis of using less dynamic data, the internal pressure of the underground space caused by soil layer displacement or distortion is comprehensively and quantitatively characterized.

[0069] Specifically, based on the boundary shape of the unstable surface sub-region, several uniformly distributed position points are selected from the boundary of the unstable surface sub-region and several randomly distributed position points are selected from the inside of the unstable surface sub-region, and the mapping position points of all the selected position points in the corresponding underground space of the unstable surface sub-region are used as several discrete underground feature points, so that each discrete underground feature point corresponds to the surface, which can ensure that the underground space covered by all discrete underground feature points truly reflects the dynamic changes of the underground soil layer. Based on the position information of all underground feature points, the displacement rate and displacement direction corresponding to all underground feature points are extracted from the fiber grating sensors pre-buried in the underground space, and the movement of each underground feature point is accurately calibrated. In addition, the squeezing force generated by soil layers of different depths has different effects on gas pipelines. In order to integrate the squeezing force generated by all soil layers, the soil layers to which all underground feature points belong are determined based on the underground depths of all underground feature points; the underground dynamic change discrete data of all underground feature points under the same soil layer are continuously fitted and predicted to determine the displacement vector of the soil layer, which refers to the vector of the displacement action of the entire soil layer; then the displacement vectors of all soil layers are integrated and analyzed to determine the displacement change trend of the soil layer in the underground space, and the displacement change trend of the soil layer is used to characterize the displacement amplitude and displacement direction of the soil layer in the future. Under the same displacement amplitude, the greater the thickness of the soil layer and / or the greater the soil density, the greater the squeezing force generated by the soil layer. In order to accurately integrate the squeezing force generated by the soil layer in the global range of the underground space, the squeezing pressure distribution information inside each soil layer in the underground space and the squeezing pressure distribution information between any two adjacent soil layers are estimated based on the physical characteristics such as the thickness and soil density of all soil layers in the underground space and the displacement change trend of the soil layer, so as to provide sufficient and reliable basis for the subsequent identification of the location point where the gas pipeline is deformed by pressure.

[0070] S300, based on the internal pressure distribution information of the soil layer and the morphological characteristic information of the gas pipeline, determine the structurally vulnerable location points of the gas pipeline; collect the air pressure data of the pipeline section associated with the structurally vulnerable location points, perform time domain analysis on the air pressure data for the entire life cycle of the pipeline operation, and predict the characteristic information of the occurrence of gas pipeline failures.

[0071] Furthermore, based on the internal pressure distribution information of the soil layer and the morphological characteristics of the gas pipeline, the structurally vulnerable locations of the gas pipeline are determined; the air pressure data of the associated pipeline sections of the structurally vulnerable locations are collected, and the air pressure data is analyzed in the time domain for the entire life cycle of the pipeline operation to predict the characteristic information of the gas pipeline failure, specifically:

[0072] Based on the internal pressure distribution information of the soil layer, determine the abnormal point group of the internal pressure effect in the underground space; based on the morphological characteristics of the extension path of the gas pipeline in the underground space, determine the structural vulnerable point group of the gas pipeline in the underground space; based on the relative position relationship between the abnormal point group of the internal pressure effect and the structural vulnerable point group, select the structurally vulnerable position points of the gas pipeline from the structural vulnerable point group;

[0073] The air pressure data of the easily affected structural points in the associated pipeline sections of the gas pipeline are collected, and the temporal and spatial changes of the air pressure data over the entire life cycle of the pipeline operation are analyzed. The location points of gas leakage faults in the associated pipeline sections and their gas leakage flow are predicted, which are used as characteristic information of gas pipeline faults.

[0074] The squeezing effect inside the soil layer will be transmitted to the gas pipeline. Considering the structural differences of the gas pipeline along the entire extension path, that is, the structural strength of the gas pipeline is greater in some parts and smaller in other parts, the gas pipeline has different anti-squeezing performance in different parts. For example, in the parts with more bending structures of the gas pipeline, its structural strength is smaller, and the corresponding anti-squeezing performance is also poor, that is, these parts are structurally fragile parts of the gas pipeline, while in the straight extension parts of the gas pipeline, its structural strength is greater, and the corresponding anti-squeezing performance is also better. In addition, the transmission distance and application area of ​​the squeezing effect inside the soil layer to the gas pipeline will also affect the probability of deformation failure of the gas pipeline.

[0075] Generally speaking, the smaller the transmission distance of the extrusion effect to a certain range on the gas pipeline and / or the larger the application area of ​​the extrusion effect to a certain range on the gas pipeline, the higher the probability of deformation failure in a certain range on the gas pipeline, that is, a certain range on the gas pipeline belongs to the range susceptible to the extrusion effect, and these ranges are more likely to have deformation failures than other ranges. These ranges can be understood as the spatial range composed of the structural vulnerable points of the gas pipeline. Specifically, based on the internal pressure distribution information of the soil layer, the position points where the internal pressure action value of the underground space is greater than the preset action threshold are determined, and these position points are collectively formed into an abnormal point group of the internal pressure action. There is also information on the curvature radius of the extension path of the gas pipeline in the underground space, and all position points on the pipeline interval whose curvature radius is less than the preset radius threshold are determined as the structural vulnerable point group of the gas pipeline in the underground space. Based on the relative distance relationship between the internal pressure action abnormal point group and the structural vulnerable point group, the Mahalanobis distance between each structural vulnerable point under the structural vulnerable point group and the internal pressure action abnormal point group is determined. If the Mahalanobis distance is less than the preset distance threshold, the structural vulnerable point is determined as the structural vulnerable point of the gas pipeline. In addition, natural gas pressure data is collected from a pipeline section of a preset length connected to a structurally vulnerable position point in the gas pipeline, and the pressure data is analyzed for temporal and spatial changes over the entire life cycle of the pipeline operation to obtain spatial distribution and temporal change information of the natural gas pressure inside the pipeline section. If the natural gas pressure at a certain position inside the pipeline section is less than a preset pressure threshold, the corresponding position is determined as the location point where the gas leakage fault occurred, and based on the time domain change information of the natural gas pressure at the location point where the gas leakage fault occurred, the gas leakage flow rate is obtained to achieve fixed-point fault identification and prediction of the gas pipeline.

[0076] See also Figure 2 As shown, the present invention provides a gas pipeline full life cycle analysis and monitoring device, which includes the following modules:

[0077] The surface morphology recognition module is used to collect surface images of the gas pipeline laying area during the entire life cycle of the pipeline operation, and obtain the surface morphology change data of the laying area from the dynamic recognition of the surface images;

[0078] An unstable area determination module, used to determine unstable sub-areas of the surface within the paving area based on the surface topography change data;

[0079] The underground soil layer change trend determination module is used to collect the underground dynamic change discrete data of the underground space corresponding to the unstable sub-area on the surface, and determine the soil layer change trend of the underground space based on the underground dynamic change discrete data;

[0080] The soil layer internal pressure distribution estimation module is used to estimate the soil layer internal pressure distribution information of the underground space based on the soil layer change trend;

[0081] A pipeline location point determination module is used to determine the structurally susceptible location points of the gas pipeline based on the internal pressure distribution information of the soil layer and the morphological characteristic information of the gas pipeline;

[0082] The fault occurrence prediction module is used to collect the air pressure data of the associated pipeline section at the structurally susceptible location point, conduct time domain analysis of the air pressure data on the entire life cycle of pipeline operation, and predict the characteristic information of gas pipeline fault occurrence.

[0083] Furthermore, the surface morphology recognition module is used to collect surface images of the gas pipeline laying area during the entire life cycle of the pipeline operation, and obtain the surface morphology change data of the laying area from the surface images through dynamic recognition, specifically:

[0084] Synchronous panoramic photography and meteorological detection are carried out on the surface of the gas pipeline laying area, so as to obtain panoramic images and meteorological data of the surface of the gas pipeline laying area during the entire life cycle of the pipeline operation;

[0085] Based on meteorological data, determine the time information of preset meteorological events in the gas pipeline laying area; based on the time information, extract a number of surface panoramic image frames from the surface panoramic image; perform surface contour recognition and contour position change recognition on all surface panoramic image frames to obtain surface morphology change data of the laying area; wherein the surface morphology change data includes contour height change data and contour direction change data of the surface corresponding to the laying area;

[0086] The unstable area determination module is used to determine the unstable sub-areas of the surface within the paving area based on the surface morphology change data, specifically:

[0087] The surface morphology change data is analyzed to determine the height fluctuation distribution information and the surface structure contour continuous state distribution information of the surface corresponding to the paving area; based on the height fluctuation distribution information and the surface structure contour continuous state distribution information, the unstable surface sub-area within the paving area is determined.

[0088] Furthermore, the underground soil layer change trend determination module is used to collect the underground dynamic change discrete data of the underground space corresponding to the unstable surface sub-area, and determine the soil layer change trend of the underground space based on the underground dynamic change discrete data, specifically:

[0089] Based on the boundary shape of the unstable surface sub-region, a number of discrete underground feature points corresponding to the underground space of the unstable surface sub-region are calibrated; based on the position information of all underground feature points, underground dynamic change discrete data corresponding to all underground feature points are collected; wherein the underground dynamic change discrete data includes the displacement rate and displacement direction corresponding to each underground feature point;

[0090] Based on the underground depth of all underground feature points, determine the soil layers to which all underground feature points belong; perform continuous fitting prediction on the discrete data of underground dynamic changes of all underground feature points under the same soil layer to determine the displacement vector of the soil layer; perform integrated analysis on the displacement vectors of all soil layers to determine the displacement change trend of the soil layers in the underground space;

[0091] The soil internal pressure distribution estimation module is used to estimate the soil internal pressure distribution information of the underground space based on the soil layer change trend, specifically:

[0092] Based on the physical characteristics of all soil layers in the underground space and the displacement change trends of the soil layers, the extrusion pressure distribution information inside each soil layer in the underground space and the extrusion pressure distribution information between any two adjacent soil layers are estimated as the internal pressure distribution information of the soil layers in the underground space.

[0093] Furthermore, the pipeline location point determination module is used to determine the structurally susceptible location points of the gas pipeline based on the internal pressure distribution information of the soil layer and the morphological characteristic information of the gas pipeline, specifically:

[0094] Based on the internal pressure distribution information of the soil layer, the abnormal point group of internal pressure in the underground space is determined; based on the morphological characteristic information of the extension path of the gas pipeline in the underground space, the structural vulnerable point group of the gas pipeline in the underground space is determined; based on the relative position relationship between the abnormal point group of internal pressure and the structural vulnerable point group, the structurally susceptible position points of the gas pipeline are screened from the structural vulnerable point group.

[0095] Furthermore, the fault occurrence prediction module is used to collect the gas pressure data of the associated pipeline section at the structurally susceptible location point, perform time domain analysis on the gas pressure data for the entire life cycle of pipeline operation, and predict the fault occurrence characteristic information of the gas pipeline, specifically:

[0096] The air pressure data of the easily affected structural points in the associated pipeline sections of the gas pipeline are collected, and the temporal and spatial changes of the air pressure data over the entire life cycle of the pipeline operation are analyzed. The location points of gas leakage faults in the associated pipeline sections and their gas leakage flow are predicted, which are used as characteristic information of gas pipeline faults.

[0097] The operation and effect of the gas pipeline full life cycle analysis and monitoring device of the present invention are corresponding to and consistent with the above-mentioned gas pipeline full life cycle analysis and monitoring method, and the gas pipeline full life cycle analysis and monitoring device will not be repeated here.

[0098] The operation and effect of the gas pipeline full life cycle analysis and monitoring device of the present invention are corresponding to and consistent with the above-mentioned gas pipeline full life cycle analysis and monitoring method, and the surface morphology recognition module, unstable area determination module, underground soil layer change trend determination module, soil layer internal pressure distribution estimation module, pipeline location point determination module, and fault occurrence prediction module of the gas pipeline full life cycle analysis and monitoring device respectively implement the same functions as the above-mentioned gas pipeline full life cycle analysis and monitoring method, and the gas pipeline full life cycle analysis and monitoring device will not be repeated here.

[0099] See also Figure 3 As shown, the present invention provides a gas pipeline full life cycle analysis and monitoring system, the system comprising:

[0100] The above-mentioned gas pipeline full life cycle analysis and monitoring device;

[0101] The early warning notification device is used to send early warning notification messages to the back-end according to the fault occurrence characteristic information predicted by the gas pipeline full life cycle analysis and monitoring device.

[0102] In the above-mentioned gas pipeline full life cycle analysis and monitoring system, the early warning notification device may be but is not limited to a portable or fixed communication base station. The communication base station can be wirelessly connected to the gas pipeline full life cycle analysis and monitoring device. When the gas pipeline full life cycle analysis and monitoring device generates fault characteristic information, the communication base station will package the fault characteristic information and convert it into an early warning notification message, and send it to the back-end, so that the staff at the back-end can promptly know the fault situation of the gas pipeline, ensuring the timeliness and accuracy of the maintenance of the gas pipeline.

[0103] Through the description of the above implementation methods, technicians in this field can clearly understand that each implementation method can be implemented by adding a necessary general hardware platform, and of course can also be implemented by combining hardware and software. Based on this understanding, the above technical solution is essentially or the part that contributes to the prior art can be embodied in the form of a computer product, and the present invention can be in the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program codes.

[0104] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it, and other embodiments may also be used. Although the present invention has been described in detail with reference to the aforementioned embodiments, ordinary technicians in this field should understand that they can still modify the technical solutions recorded in the aforementioned embodiments, or replace some of the technical features therein with equivalents. However, these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A gas pipeline full life cycle analysis and monitoring method, characterized in that: The method comprises the following steps: Collecting surface images of the gas pipeline laying area during the entire life cycle of the pipeline operation, and dynamically identifying the surface morphology change data of the laying area from the surface images; determining the unstable surface sub-area in the laying area based on the surface morphology change data; Collecting the underground dynamic change discrete data of the underground space corresponding to the unstable surface sub-area, determining the soil layer change trend of the underground space based on the underground dynamic change discrete data; estimating the internal pressure distribution information of the soil layer of the underground space based on the soil layer change trend, which is specifically: Based on the boundary shape of the unstable surface sub-region, a number of discrete underground feature points corresponding to the underground space of the unstable surface sub-region are calibrated; based on the position information of all underground feature points, underground dynamic change discrete data corresponding to all underground feature points are collected; wherein the underground dynamic change discrete data includes the displacement rate and displacement direction corresponding to each underground feature point; Based on the underground depth of all underground feature points, determine the soil layers to which all underground feature points belong; perform continuous fitting prediction on the underground dynamic change discrete data of all underground feature points under the same soil layer to determine the displacement vector of the soil layer; perform integrated analysis on the displacement vectors of all soil layers to determine the displacement change trend of the soil layer in the underground space; Based on the physical characteristics of all soil layers in the underground space and the displacement change trend of the soil layers, the squeezing pressure distribution information inside each soil layer in the underground space and the squeezing pressure distribution information between any two adjacent soil layers are estimated as the internal pressure distribution information of the soil layers in the underground space; wherein the physical characteristics include the thickness and soil density of all soil layers in the underground space; Based on the internal pressure distribution information of the soil layer and the morphological characteristic information of the gas pipeline, the structural vulnerable position point of the gas pipeline is determined; the air pressure data of the pipeline section associated with the structural vulnerable position point is collected, and the time domain analysis of the air pressure data for the entire life cycle of the pipeline operation is performed to predict the fault occurrence characteristic information of the gas pipeline, which is specifically: Based on the internal pressure distribution information of the soil layer, determine the abnormal point group of internal pressure action of the underground space; based on the morphological characteristic information of the extension path of the gas pipeline in the underground space, determine the structural vulnerable point group of the gas pipeline in the underground space; based on the relative position relationship between the abnormal point group of internal pressure action and the structural vulnerable point group, screen the structural vulnerable position points of the gas pipeline from the structural vulnerable point group; The air pressure data of the pipeline section associated with the structure's susceptible location in the gas pipeline is collected, and the time domain and spatial domain change analysis of the air pressure data over the entire life cycle of the pipeline operation is performed to predict the location point where the gas leakage fault occurs and the gas leakage flow rate of the associated pipeline section, which is used as the characteristic information of the gas pipeline fault.

2. The method according to claim 1, characterized in that The collecting of surface images of the gas pipeline laying area during the entire life cycle of the pipeline operation, and obtaining surface morphology change data of the laying area from the surface images by dynamic recognition; and determining the unstable surface sub-area in the laying area based on the surface morphology change data, specifically: Performing synchronous panoramic photography and meteorological detection on the surface corresponding to the gas pipeline laying area, and obtaining the surface panoramic images and meteorological data of the gas pipeline laying area during the entire life cycle of the pipeline operation; Based on the meteorological data, determining the time information of a preset meteorological event occurring in the gas pipeline laying area; Based on the time information, a plurality of surface panoramic image frames are extracted from the surface panoramic image; surface contour recognition and contour position change recognition are performed on all surface panoramic image frames to obtain surface topography change data of the paving area; wherein the surface topography change data includes contour height change data and contour direction change data of the surface corresponding to the paving area; The surface morphology change data is analyzed to determine the height fluctuation distribution information and the surface structure contour continuous state distribution information of the surface corresponding to the paving area; based on the height fluctuation distribution information and the surface structure contour continuous state distribution information, the unstable sub-area of ​​the surface within the paving area is determined.

3. A gas pipeline full life cycle analysis and monitoring device, characterized in that: The device comprises the following modules: A surface morphology recognition module is used to collect surface images of the gas pipeline laying area during the entire life cycle of the pipeline operation, and dynamically identify the surface morphology change data of the laying area from the surface images; An unstable region determination module, used for determining an unstable sub-region of the surface within the paving area based on the surface topography change data; The underground soil layer change trend determination module is used to collect the underground dynamic change discrete data of the underground space corresponding to the unstable surface sub-area, and determine the soil layer change trend of the underground space based on the underground dynamic change discrete data, which is specifically: Based on the boundary shape of the unstable surface sub-region, a number of discrete underground feature points corresponding to the underground space of the unstable surface sub-region are calibrated; based on the position information of all underground feature points, underground dynamic change discrete data corresponding to all underground feature points are collected; wherein the underground dynamic change discrete data includes the displacement rate and displacement direction corresponding to each underground feature point; Based on the underground depth of all underground feature points, determine the soil layers to which all underground feature points belong; perform continuous fitting prediction on the underground dynamic change discrete data of all underground feature points under the same soil layer to determine the displacement vector of the soil layer; perform integrated analysis on the displacement vectors of all soil layers to determine the displacement change trend of the soil layer in the underground space; The soil layer internal pressure distribution estimation module is used to estimate the soil layer internal pressure distribution information of the underground space based on the soil layer change trend, which is specifically: Based on the physical characteristics of all soil layers in the underground space and the displacement change trend of the soil layers, the squeezing pressure distribution information inside each soil layer in the underground space and the squeezing pressure distribution information between any two adjacent soil layers are estimated as the internal pressure distribution information of the soil layers in the underground space; wherein the physical characteristics include the thickness and soil density of all soil layers in the underground space; The pipeline location point determination module is used to determine the structurally susceptible location point of the gas pipeline based on the internal pressure distribution information of the soil layer and the morphological characteristic information of the gas pipeline, which is specifically: Based on the internal pressure distribution information of the soil layer, determine the abnormal point group of internal pressure action of the underground space; based on the morphological characteristic information of the extension path of the gas pipeline in the underground space, determine the structural vulnerable point group of the gas pipeline in the underground space; based on the relative position relationship between the abnormal point group of internal pressure action and the structural vulnerable point group, screen the structural vulnerable position points of the gas pipeline from the structural vulnerable point group; The fault occurrence prediction module is used to collect the gas pressure data of the associated pipeline section of the vulnerable position point of the structure, perform time domain analysis on the gas pressure data for the entire life cycle of the pipeline operation, and predict the fault occurrence characteristic information of the gas pipeline, which is specifically: The air pressure data of the pipeline section associated with the structure's susceptible location in the gas pipeline is collected, and the time domain and spatial domain change analysis of the air pressure data over the entire life cycle of the pipeline operation is performed to predict the location point where the gas leakage fault occurs and the gas leakage flow rate of the associated pipeline section, which is used as the characteristic information of the gas pipeline fault.

4. The device according to claim 3, characterized in that The surface morphology recognition module is used to collect surface images of the gas pipeline laying area during the entire life cycle of the pipeline operation, and dynamically identify the surface morphology change data of the laying area from the surface images, specifically: Performing synchronous panoramic photography and meteorological detection on the surface corresponding to the gas pipeline laying area, and obtaining the surface panoramic images and meteorological data of the gas pipeline laying area during the entire life cycle of the pipeline operation; Based on the meteorological data, determining the time information of a preset meteorological event occurring in the gas pipeline laying area; Based on the time information, a plurality of surface panoramic image frames are extracted from the surface panoramic image; surface contour recognition and contour position change recognition are performed on all surface panoramic image frames to obtain surface topography change data of the paving area; wherein the surface topography change data includes contour height change data and contour direction change data of the surface corresponding to the paving area; The unstable area determination module is used to determine the unstable surface sub-area in the paving area based on the surface morphology change data, specifically: The surface morphology change data is analyzed to determine the height fluctuation distribution information and the surface structure contour continuous state distribution information of the surface corresponding to the paving area; based on the height fluctuation distribution information and the surface structure contour continuous state distribution information, the unstable sub-area of ​​the surface within the paving area is determined.

5. A gas pipeline full life cycle analysis and monitoring system, characterized in that: The system comprises: The gas pipeline full life cycle analysis and monitoring device as described in any one of claims 3-4; The early warning notification device is used to send an early warning notification message to the backend according to the fault occurrence characteristic information predicted by the gas pipeline full life cycle analysis and monitoring device.

Images