A suspected leakage point analysis method and analysis device

Abstract

The present invention provides a suspected leakage point analysis method and analysis device, which solves the technical problem that the existing leakage point analysis method has poor adaptability in urban environments. The method includes: forming periodic inspection data within a determined range on the extension path of the gas pipeline according to the time series and coordinate dimensions; determining the type of interference source according to the time series correlation of the periodic inspection data and excluding the inspection data of the corresponding interference source to form inspection data updates; determining the suspected leakage source according to the spatial correlation of the periodic inspection data, and determining the leakage point according to the inspection data of the suspected leakage source. The suspected leakage point is located and the inspection data is analyzed from two dimensions of time and space. By combining the individual changes and associated changes on the time scale with the geographic coordinates, the invalid inspection data of the urban interference source in the leakage point analysis process is excluded, and the leakage point is distinguished and clarified. This enables the ultra-high precision gas leak rapid detection method of the methane / ethane analyzer to be effectively implemented in the urban environment.

Description

Technical Field

[0001] The present invention relates to the technical field of gas leakage detection, and in particular to a suspected leakage point analysis method and analysis device. Background Art

[0002] In existing technologies, laser absorption spectroscopy combined with Beidou precise positioning, ultrasonic wind direction and speed measurement and meteorological data can accurately analyze and identify the composition, concentration, temperature and humidity, location and diffusion trend of methane / ethane leaks in meteorologically stable open environments such as rural areas. For example, the inspection data generated by ABB methane / ethane analyzers are graphical data such as Figure 1 As shown. Figure 1 During the inspection process, the air sample composition is detected and analyzed in real time to form a fan-shaped area diagram containing the gas composition, and the inspection information such as the location, range and concentration of the gas leakage is identified based on the fan-shaped area.

[0003] Gas pipelines in cities are unevenly distributed. This is primarily reflected in the fact that the number and diameter of pipelines often fluctuate in line with user demand, resulting in a nonlinear distribution across the city. While the urban gas pipeline network is traceable, the complex road traffic environment, the diverse range of municipal facilities, and the complex wind conditions created by the towering skyscrapers can significantly interfere with the identification of accidental leaks, reducing the reliability of analytical data, leading to errors in leak location identification, and reducing operational and maintenance efficiency. Summary of the Invention

[0004] In view of the above problems, embodiments of the present invention provide a suspected leakage point analysis method and analysis device to solve the technical problem that the existing leakage point analysis method has poor adaptability in urban environments.

[0005] The suspected leak point analysis method according to an embodiment of the present invention includes:

[0006] Generate periodic inspection data within a certain range on the gas pipeline extension path based on the time series dimension and the coordinate dimension;

[0007] Determine the interference source type based on the time sequence correlation of periodic inspection data and exclude the inspection data of the corresponding interference source to form inspection data update;

[0008] The suspected leakage source is determined based on the spatial correlation of the periodic inspection data, and the leakage point is determined based on the inspection data of the suspected leakage source.

[0009] In one embodiment of the present invention, the forming of periodic inspection data within a certain range on the gas pipeline extension path includes:

[0010] Determine the fixed inspection range within the continuous inspection cycle, and form the inspection driving coefficient based on the gas pipeline extension path, meteorological wind speed and extension path wind environment;

[0011] During the inspection process, adjust the vehicle speed according to the inspection driving coefficient;

[0012] Periodic inspection data is generated based on the inspection data generated at the controlled vehicle speed.

[0013] In one embodiment of the present invention, the forming of inspection data update by excluding the inspection data of the corresponding interference source includes:

[0014] The first part of the suspected leakage point set is determined by clustering the time series characteristics and road location characteristics of each inspection data in each inspection cycle;

[0015] Determine a second set of suspected leakage points based on clustering the time series characteristics and single component characteristics of each inspection data in each inspection cycle;

[0016] Determine a third set of suspected leakage points based on clustering features between at least two components of each inspection data in each inspection cycle;

[0017] The inspection data is compared based on the timing characteristics, location characteristics and component characteristics of each suspected leakage point set to determine the suspected fixed interference source, and the periodic inspection data is updated for the first time based on the suspected fixed interference source.

[0018] In one embodiment of the present invention, the rule for determining a suspected fixed interference source includes:

[0019] - Based on the time information and road location of each inspection data in the suspected leakage point set, combined with GIS resources, the suspected fixed interference source is determined to be a ground gas filling station or underground biogas tank or reservoir near the cluster location;

[0020] - Based on the two-component ratio information and time information of each inspection data in the suspected leakage point set, combined with the location and GIS resources, the suspected fixed interference source is determined to be a nearby ground gas filling station or underground biogas pool or storage;

[0021] -Based on the single component information and road location in the suspected leakage point set, combined with GIS resources, the suspected fixed interference source is determined to be a polluted low-lying water source near the cluster location;

[0022] -Based on the single component concentration information, time information and location information of each inspection data in the suspected leakage point set, combined with GIS resources, the suspected fixed interference source is determined to be a polluted low-lying water source near the cluster location.

[0023] In one embodiment of the present invention, the present invention further includes:

[0024] Quantify the linear trend of changes in inspection vehicle speed and concentration of a single harmful component in inspection data within a single inspection cycle;

[0025] Quantify the linear trend of the change in inspection vehicle speed and the concentration ratio of harmful components in the inspection data within a single inspection cycle;

[0026] Quantify the linear trend of inspection direction changes and sector area direction changes in inspection data within a single inspection cycle;

[0027] The suspected mobile interference source is determined based on the degree of adaptation between the inspection data and the inspection vehicle speed, and the periodic inspection data is updated for the second time based on the suspected mobile interference source.

[0028] In one embodiment of the present invention, the rules for determining the suspected mobile interference source include:

[0029] -Based on the changes in composition and concentration in the inspection data before and after the inspection vehicle speed reaches zero in a single inspection cycle, the suspected mobile interference source is determined to be a moving vehicle that changes its synchronous driving;

[0030] - Determine whether the suspected mobile interference source is a side-by-side or leading moving vehicle based on the degree of match between the position interval of inspection data with the same concentration of individual harmful components in a single inspection cycle and the speed of the inspection vehicle;

[0031] -Determine the suspected mobile interference source as a side-by-side or leading moving vehicle based on the degree of match between the position interval of inspection data with the same ratio of concentration of the same harmful component in a single inspection cycle and the speed of the inspection vehicle;

[0032] - According to the change of the direction of the fan-shaped area in the inspection data in a single inspection cycle with the speed direction of the inspection vehicle, it is determined that the suspected mobile interference source is a synchronously moving vehicle.

[0033] In one embodiment of the present invention, determining a suspected leakage source based on the spatial correlation of periodic inspection data and determining the leakage point based on the inspection data of the suspected leakage source includes:

[0034] Determine the same type of alternative sector areas of the suspected leakage point based on the methane-ethane concentration ratio in the periodic inspection data;

[0035] Cluster the pointing directions according to the directions of the same type of alternative fan-shaped areas to form the reference directions of the suspected leakage points;

[0036] Forming a reference range of the suspected leakage point according to the area of ​​the candidate fan-shaped area forming the reference direction of the suspected leakage point;

[0037] Determine the suspected leakage points of underground gas pipeline resources based on the reference range.

[0038] The suspected leakage point analysis device according to an embodiment of the present invention includes:

[0039] A memory for storing program codes used in the processing of the suspected leak point analysis method described above;

[0040] A processor is configured to execute the program code.

[0041] The suspected leakage point analysis device according to an embodiment of the present invention includes:

[0042] An inspection data matching module is used to generate periodic inspection data within a certain range on the gas pipeline extension path according to the time series dimension and the coordinate dimension;

[0043] Interference data exclusion module, used to determine the type of interference source according to the time sequence correlation of periodic inspection data and exclude the inspection data of the corresponding interference source to form inspection data update;

[0044] The suspected point determination module is used to determine the suspected leakage source based on the spatial correlation of the periodic inspection data, and to determine the leakage point based on the inspection data of the suspected leakage source.

[0045] The suspected leak point analysis method and analysis device of the embodiment of the present invention locates the suspected leak point through inspection data analysis from both time and space dimensions. By combining the individual and associated changes in the inspection data on a temporal scale with geographic coordinates, invalid inspection data from urban interference sources is eliminated during the leak point analysis process. The individual and associated change trends in the spatial scale of valid inspection data are combined with pipeline geographic information to distinguish suspected leak points and identify the leak point. This allows the ultra-high-precision rapid gas leak detection method of the methane / ethane analyzer to be effectively implemented in urban environments, forming a basis for determining the adequate scheduling of operation and maintenance resources. BRIEF DESCRIPTION OF THE DRAWINGS

[0046] Figure 1 The figure shows a graphical diagram of inspection data generated by an analyzer in the prior art.

[0047] Figure 2 FIG2 is a flow chart of a suspected leakage point analysis method according to an embodiment of the present invention.

[0048] Figure 3 FIG2 is a schematic diagram of the structure of a suspected leakage point analysis device according to an embodiment of the present invention. DETAILED DESCRIPTION

[0049] To make the objectives, technical solutions, and advantages of the present invention more clear and understandable, the present invention is further described below with reference to the accompanying drawings and specific embodiments. Obviously, the embodiments described are only some of the embodiments of the present invention, not all of them. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making any creative efforts are within the scope of protection of the present invention.

[0050] A suspected leak point analysis method according to an embodiment of the present invention is as follows: Figure 2 As shown. Figure 1 In this embodiment, the present invention includes:

[0051] Step 100: Generate periodic inspection data within a certain range on the gas pipeline extension path according to the time series dimension and the coordinate dimension.

[0052] Those skilled in the art will understand that the inspection data that can be obtained by using a comprehensive methane / ethane analyzer on an inspection vehicle includes, but is not limited to, real-time inspection data such as coordinates, gas flow rate, gas composition, and component concentration during the inspection cycle, as well as real-time sector area data of the hazardous gas distribution generated by the analyzer based on a built-in algorithm using real-time inspection data. The sector area reflects the diffusion state of the hazardous gas within a limited time, including the diffusion range, diffusion angle, etc. The inspection vehicle conducts periodic inspections based on the pipeline extension data reflected in the underground gas pipeline network data combined with the gas pipeline extension path formed by the road traffic data. For example, the same section of road is inspected in the same direction at the same time every day. Relevant inspection data content can be obtained by retrieving data through time series and coordinates from the relational data storage structure. The inspection cycle will be planned according to the inspection area, and will also be formed based on the obtained inspection data or the inspection analysis results, such as key inspections of key areas determined based on the inspection analysis results.

[0053] Step 200: Determine the type of interference source according to the time sequence correlation of periodic inspection data and exclude the inspection data of the corresponding interference source to form inspection data update.

[0054] Those skilled in the art will understand that once interference factors appear in the city, the analytical instrument will generate false alarm information or incorrectly identify the sector area based on the collected inspection data. The volatile components of concealed projects, underground ditches that harbor filth, surface depressions that accumulate and deteriorate, and distributed energy stations can all form fixed interference factors that cause the analytical instrument to make misjudgments. A large number of vehicles that do not meet the exhaust gas environmental protection requirements or mobile equipment with similar component leaks can form random interference factors. The type of interference source is closely related to the formation process. The type of interference source is identified based on the temporal change characteristics of periodic inspection data, and the interference data is determined based on the type of interference source to achieve clear elimination of interference factors during the inspection process. Temporal correlation includes but is not limited to the temporal changes of the same components, the temporal changes of related components, etc.

[0055] Step 300: Determine a suspected leakage source based on the spatial correlation of periodic inspection data, and determine the leakage point based on the inspection data of the suspected leakage source.

[0056] Those skilled in the art can understand that in cities, due to the limitations of the sensitivity of analytical instruments, the complex building wind environment causes errors in the identification of fan-shaped areas, which are mainly reflected in the obvious deviation of the identified fan-shaped areas from the existing pipeline data, the wrong direction of the fan-shaped areas, the increased dispersion of fan-shaped areas of different components, and the deviation of the alarm position from the sector area. In the process of dissipation to form fan-shaped areas, the disturbed leaked gas and the leakage point still have a characteristic change correlation within the spatial scale. According to the change characteristics of other inspection data in the sector area space in the periodic inspection data, the related suspected discharge port points are identified to achieve the clear elimination of interference factors during the inspection process. Spatial correlation includes but is not limited to the morphology and changes of the fan-shaped area, the morphology maintenance and changes of the fan-shaped area for underground pipelines, the superposition state of the fan-shaped area, etc.

[0057] The suspected leakage point analysis method of the embodiment of the present invention locates the suspected leakage point through inspection data analysis from two dimensions: time and space. By combining the individual changes and associated changes of the inspection data on a time scale with the geographic coordinates, invalid inspection data of urban interference sources are eliminated during the leakage point analysis process. The individual change trends and associated change trends of the valid inspection data on a spatial scale are combined with the pipeline geographic information to distinguish suspected leakage points and identify the leakage points. This allows the methane / ethane analyzer's ultra-high precision (PPB level) rapid gas leak detection method to be effectively implemented in an urban environment, forming a basis for determining the full scheduling of operation and maintenance resources.

[0058] The processing in the present invention can use general clustering algorithms such as Kmeans and Wkmeans to perform cluster identification of components, angles, distances, and directions, and can form weighted processing of important data and dimensions to form more efficient data convergence and precision adjustment.

[0059] like Figure 2 As shown, in one embodiment of the present invention, step 100 includes:

[0060] Step 110: Determine a fixed inspection range within a continuous inspection cycle, and form an inspection driving coefficient based on the gas pipeline extension path, meteorological wind speed, and extension path wind environment.

[0061] Those skilled in the art will understand that by setting an inspection cycle within the inspection range on the fixed gas pipeline extension path, the inspection data density and real-time performance can be improved by changing the inspection frequency, thereby obtaining a higher information density for data analysis. The background wind speed during the inspection process can be obtained through the local meteorological wind speed, and the dynamic wind speed of the wind environment on the extension path can be obtained through the anemometer. The background wind speed is mainly used, and the dynamic wind speed is used to form the wind speed weighting of the local environment on the extension path. An inspection driving coefficient can be established between the inspection vehicle's driving speed and the ambient wind speed, and the inspection vehicle's driving speed can be adjusted by the inspection driving coefficient. The dynamic wind speed of the extension path wind environment can be obtained through wind tunnel simulation data of the building group wind environment in the municipal planning data or historical experience statistical data.

[0062] Step 120: During the inspection process, the vehicle speed is adjusted according to the inspection driving coefficient.

[0063] The inspection travel coefficient is related to the local environment along the gas pipeline extension path during the inspection. By adjusting the vehicle speed during the inspection using the inspection travel coefficient, the integrated methane / ethane analyzer maintains a relatively stable ambient speed range during sample collection. This ensures that the fan-shaped data generated by the analyzer during the inspection is stable and complete, avoiding fan-shaped areas where the leakage concentration is sufficient to generate an alarm but is disrupted by excessive wind turbulence and does not generate relevant data. This reduces the likelihood of disorganization and disconnection of relevant inspection data during subsequent identification and analysis of suspected leaks, which increases the difficulty of identification.

[0064] Step 130: Generate periodic inspection data based on the inspection data generated at the controlled vehicle speed.

[0065] Sector regions are graphical representations of related data types generated by the analyzer processing sampled data at the same moment. Combining sector regions with urban GIS (Geographic Information System) resources and inspection coordinates for the underground pipeline network can create a graphical representation of suspected leak points or leak sources along the gas pipeline extension. Using sector regions as data structural units, a series of time-series sector region inspection data is generated during each inspection cycle, further forming periodic inspection data.

[0066] The suspected leak point analysis method of this embodiment of the present invention establishes an inspection rate compensation mechanism based on the effective inspection accuracy of equipment and instruments, thereby enhancing the availability and accuracy of inspection sample collection. This ensures that during normal inspections, the interference of local urban wind conditions on inspection data is largely within a tolerable range, ensuring that the inspection data composition meets the integrity requirements for subsequent assessment and analysis.

[0067] like Figure 2 As shown, in one embodiment of the present invention, step 200 includes:

[0068] Step 210: Determine the first set of suspected leakage points based on clustering of the time series characteristics and road location characteristics of each inspection data in each inspection cycle, so as to identify the scope of the fixed pollution source.

[0069] Those skilled in the art will understand that the inspection data is mainly aimed at the locations where hazardous gas leaks are suspected to have occurred. Determining the coordinate position of each inspection data in each inspection cycle can mark the suspected leakage points. Specific buildings, facilities or terrains can form slight continuous overflow, retention and accumulation of harmful gas components. By clustering the formation time characteristics of the suspected leakage points to the specific buildings, facilities or terrains nearby, the correlation between the inspection data of the suspected leakage and the timeliness of the urban-specific environment near the road can be quantified, and the inspection data of the suspected leakage points that are not gas pipeline leakage factors can be highlighted. By clustering the road location characteristics of the suspected leakage points to the specific buildings, facilities or terrains nearby, the correlation between the location of the inspection data of the suspected leakage and the urban-specific environment near the road can be quantified, and the inspection data of the suspected leakage points that are not gas pipeline leakage factors can be highlighted.

[0070] Step 220: Determine a second set of suspected leakage points based on clustering the time series features and single component features of each inspection data in each inspection cycle to identify the type of fixed pollution source.

[0071] Those skilled in the art will understand that a single harmful gas component in the inspection data may be a slight continuous overflow, retention and accumulation of incidental harmful gas components formed by specific buildings, facilities or terrain in the urban environment. By clustering the formation time characteristics of the suspected leakage points to the specific buildings, facilities or terrain nearby, the time-sensitive correlation between the inspection data of the suspected leakage and the city-specific environment near the road can be quantified, and the inspection data of the suspected leakage points with non-gas pipeline leakage factors can be highlighted. By clustering the single component characteristics of the suspected leakage points, such as component type and concentration, to the specific buildings, facilities or terrain nearby, the correlation between the inspection data of the suspected leakage and the components of the city-specific environment near the road can be quantified, and the inspection data of the suspected leakage points with non-gas pipeline leakage factors can be highlighted.

[0072] Step 230: Determine a third set of suspected leakage points based on clustering features between at least two components of each inspection data in each inspection cycle, so as to identify differences in fixed pollution sources.

[0073] Those skilled in the art will understand that if a single inspection data unit includes data on at least two hazardous components, then the ratio of these components is correlated with the suspected leak factor. Clustering these components based on their ratios, such as the concentration ratios of two gas components or their concentrations, to specific nearby buildings, facilities, or terrain can quantify the correlation between the inspection data of suspected leaks and the components of the urban environment near the road, highlighting the inspection data of suspected leak points that are not gas pipeline leak factors.

[0074] Step 240: perform inspection data comparison based on the timing characteristics, location characteristics, and component characteristics of each suspected leakage point set to determine the suspected fixed interference source, and update the periodic inspection data for the first time based on the suspected fixed interference source.

[0075] In one embodiment of the present invention, the rules for comparing inspection data to determine suspected fixed interference sources include:

[0076] -Based on the time information and road location of each inspection data in the suspected leakage point set, combined with GIS resources, the suspected fixed interference source is determined to be the ground gas filling station or underground biogas pool or storage near the cluster location.

[0077] When the inspection time and location of each inspection data in the set of suspected leakage points have clustered time ranges and clustered locations, and when the clustered time ranges are the same and the clustered location ranges are convergent in each inspection cycle, the type of suspected fixed interference source that forms the inspection data can be determined in combination with the local GIS resources of the city.

[0078] -Based on the two-component ratio information and time information of each inspection data in the suspected leakage point set, combined with the location and GIS resources, the suspected fixed interference source is determined to be a nearby ground gas filling station or underground biogas pool or storage.

[0079] As an independent or further verified rule, when there is a clustering time range and clustering ratio in the set of suspected leakage points, and when the clustering time range is the same in each inspection cycle and there is convergence in the clustering location range, the type of suspected fixed interference source that forms the inspection data can be determined in combination with the local GIS resources of the city.

[0080] The above rules can be verified through manual verification. ABB methane / ethane analyzers, with their sensitivity (less than 1 PPM), can detect even slight releases of harmful components from industrial settings outside of gas facilities. During inspections, leak fan-shaped areas are detected around surface oil and gas stations or underground biogas reservoirs. The inspection data, which includes periodic or persistent leaks, leak composition, and leak location, can be used to determine the location of surface oil and gas stations or underground biogas reservoirs and identify the type of suspected fixed interference sources.

[0081] -Based on the single component information and road location in the suspected leakage point set, combined with GIS resources, the suspected fixed interference source is determined to be a polluted low-lying water source near the cluster location.

[0082] When a single component of each inspection data in the suspected leakage point set has a clustered location, the type of the suspected fixed interference source forming the inspection data is determined in combination with the GIS resource terrain information of the clustered location.

[0083] -Based on the single component concentration information, time information and location information of each inspection data in the suspected leakage point set, combined with GIS resources, the suspected fixed interference source is determined to be a polluted low-lying water source near the cluster location.

[0084] When the concentration of a single component of each inspection data in the suspected leakage point set shows a gradient change at different time periods at the same location, the type of the suspected fixed interference source forming the inspection data is determined in combination with the GIS resource terrain information of the cluster location.

[0085] The above rules can be verified through manual verification. The sensitivity of ABB's methane / ethane analyzers (within 1 PPM) can identify hazardous volatilization from roadside sewage sources, sewage wells, or shallow puddles on roads. During inspections, leak fan-shaped areas or abnormal alarms are generated. By analyzing the cascade of changes in individual components in the inspection data over different periods and the location and topography, combined with necessary meteorological information, the location of the accumulated water and the type of suspected fixed interference source can be determined.

[0086] - Screen out and update the inspection data of suspected fixed interference sources to form new periodic inspection data.

[0087] After the suspected fixed interference source is determined, the inspection data generated by the suspected fixed interference source is filtered out to form the first update of the periodic inspection data.

[0088] Step 250: quantify the linear trend of the change in the inspection vehicle speed and the change in the concentration of a single harmful component in the inspection data within a single inspection cycle.

[0089] The quantification process involves quantifying the concentration trends of the same component in inspection data at different locations within a single inspection cycle as the inspection vehicle speed changes. Quantification includes, but is not limited to, changes in methane or ethane concentration values, concentration changes at different speed levels, and concentration changes within continuous time segments.

[0090] Step 260: quantify the linear trend of the change in the inspection vehicle speed and the change in the concentration ratio of the harmful components in the inspection data within a single inspection cycle.

[0091] The quantification process involves quantifying the changing trends in the concentration ratios of the same components in the inspection data at different locations within a single inspection cycle, as the inspection vehicle speed changes. This includes, but is not limited to, the changes in the concentration ratios of methane and ethane, the changes in concentration ratios at different speed levels, and the changes in concentration ratios within continuous time segments.

[0092] Step 270: quantify the linear trend of the change in the inspection direction and the change in the direction of the fan-shaped area in the inspection data within a single inspection cycle.

[0093] The quantification process involves quantifying the changing trends of the sector-shaped area directions in the inspection data as the inspection vehicle speed direction changes within a single inspection cycle. The quantified content includes, but is not limited to, the changes in the sector-shaped area directions before and after the vehicle speed direction changes, and the changes in the sector-shaped area directions before and after the vehicle speed step changes.

[0094] Step 280: Determine the suspected mobile interference source based on the degree of adaptation between the inspection data and the inspection vehicle speed, and update the periodic inspection data for the second time based on the suspected mobile interference source.

[0095] During the inspection process, large trucks, motorcycles, cars, or gas buses that emit substandard exhaust gases (methane, ethane, or other gases) may create alarm, suspected gas source, or natural gas source fan-shaped areas when they are parallel to or following the inspection vehicle. Inspection data is generated by collecting samples at the time and location of detection of harmful components.

[0096] In one embodiment of the present invention, the rules for determining the suspected mobile interference source using the (linear) adaptation degree between the inspection data and the inspection vehicle speed include:

[0097] -Based on the changes in components and concentrations in the inspection data before and after the inspection vehicle speed reaches zero in a single inspection cycle, the suspected mobile interference source is determined to be a moving vehicle that changes its synchronous driving.

[0098] When the inspection vehicle decelerates, stops, and then accelerates, inspection data showing changes in composition and concentration can be used to determine that the suspected mobile interference source is a synchronously traveling moving vehicle that changes its synchronous direction.

[0099] -Determine the suspected mobile interference source as a parallel or leading moving vehicle based on the degree of match between the position interval of the inspection data with the same concentration of individual harmful components in the inspection data in a single inspection cycle and the speed of the inspection vehicle.

[0100] When the speed of the inspection vehicle and the position interval forming the inspection data have the same linear extension trend, it can be determined that the suspected mobile interference source is a parallel or leading moving vehicle.

[0101] -The suspected mobile interference source is determined to be a side-by-side or leading moving vehicle based on the degree of matching between the position interval of the inspection data with the same ratio of the concentration of the same harmful component in a single inspection cycle and the speed of the inspection vehicle.

[0102] When the speed of the inspection vehicle and the position interval of the inspection data that form the same ratio of the concentration of the same harmful component have the same linear extension trend, it can be determined that the suspected mobile interference source is a number of moving vehicles side by side or in front.

[0103] - According to the change of the direction of the fan-shaped area in the inspection data in a single inspection cycle with the speed direction of the inspection vehicle, it is determined that the suspected mobile interference source is a synchronously moving vehicle.

[0104] When the direction of the fan-shaped area in the inspection data changes synchronously with the speed direction of the inspection vehicle, it can be determined that the suspected mobile interference sources are several moving vehicles side by side or leading.

[0105] The above rules can be verified by manual judgment. At the same time, the mutual verification process of mobile interference sources between cycles is formed by the degree of adaptation of the inspection data and the inspection vehicle speed in each adjacent inspection cycle, so as to improve the identification accuracy of suspected mobile interference sources.

[0106] - Screen and update the inspection data of suspected mobile interference sources to form new periodic inspection data.

[0107] After the suspected mobile interference source is determined, the inspection data generated by the suspected mobile interference source is screened out to form a second update of the periodic inspection data.

[0108] like Figure 2 As shown, in one embodiment of the present invention, step 300 includes:

[0109] Step 310: Determine candidate sector areas of the same type as the suspected leakage point based on the methane-ethane concentration ratio in the periodic inspection data.

[0110] The sector areas (data units) in the recent adjacent periodic inspection data whose methane-ethane concentration ratio is within the threshold range are selected to form the same type of candidate sector areas, which are used to screen the inspection data of the same type of leaked gas in the periodic inspection data.

[0111] Step 320: Cluster the pointing directions according to the directions of the candidate fan-shaped areas of the same type to form reference directions of the suspected leakage points.

[0112] Those skilled in the art can understand that the fan-shaped area, as a data structure unit, identifies the direction of diffusion of the leakage sample, that is, the fan-shaped area is a fan-shaped area formed from the leakage point from low to high after the leakage sample diffuses, and the direction of the fan-shaped area toward the leakage point can be obtained from the data structure of the fan-shaped area.

[0113] In one embodiment of the present invention, when sector-shaped areas of different inspection cycles overlap, the directional weight of the overlapping sector-shaped area is defaulted to be higher.

[0114] Step 330: forming a reference range of the suspected leakage point according to the area of ​​the candidate fan-shaped region forming the reference direction of the suspected leakage point.

[0115] The contour data of the reference range of the suspected leak point is obtained based on the area of ​​the candidate sector region. The contour data includes a larger probability diameter and a smaller probability diameter.

[0116] Step 340: Determine the suspected leakage point of the underground gas pipeline resource according to the reference range.

[0117] Combined with the historical layout data of underground gas pipeline resources and operational data such as pipe diameter, pressure, flow rate and composition, the suspected pipelines and suspected leakage points within the reference range of the suspected leakage points are determined.

[0118] An embodiment of the present invention provides a suspected leak point analysis device, comprising:

[0119] A memory for storing program codes used in the processing of the suspected leak point analysis method of the above embodiment;

[0120] The processor is used to execute the program code in the processing of the suspected leakage point analysis method of the above embodiment.

[0121] The processor can adopt a DSP (Digital Signal Processor) digital signal processor, FPGA (Field-Programmable Gate Array) field programmable gate array, MCU (Microcontroller Unit) system board, SoC (system on a chip) system board or PLC (Programmable Logic Controller) minimum system including I / O, or adopt remote or cloud computing power.

[0122] An embodiment of the invention is a device for analyzing suspected leakage points. Figure 3 As shown. Figure 3 In this embodiment, the present invention includes:

[0123] The inspection data matching module 10 is used to generate periodic inspection data within a certain range on the gas pipeline extension path according to the time series dimension and the coordinate dimension;

[0124] Interference data exclusion module 20, used to determine the type of interference source according to the time sequence correlation of periodic inspection data and exclude the inspection data of the corresponding interference source to form inspection data update;

[0125] The suspected point determination module 30 is used to determine the suspected leakage source according to the spatial correlation of the periodic inspection data, and determine the leakage point according to the inspection data of the suspected leakage source.

[0126] like Figure 3 As shown, in one embodiment of the present invention, the inspection data matching module 10 includes:

[0127] The adjustment setting unit 11 is used to determine a fixed inspection range within a continuous inspection cycle and form an inspection driving coefficient according to the gas pipeline extension path, meteorological wind speed and extension path wind environment;

[0128] An adjustment control unit 12 is used to adjust the vehicle speed during the inspection according to the inspection driving coefficient;

[0129] The data integration unit 13 is configured to generate periodic inspection data based on the inspection data generated at the controlled vehicle speed.

[0130] like Figure 3 As shown, in one embodiment of the present invention, the interference data elimination module 20 includes:

[0131] A first clustering data unit 21 is configured to determine a first set of suspected leakage points based on clustering of the time series characteristics and road location characteristics of each inspection data in each inspection cycle;

[0132] The second clustering data unit 22 is used to determine a second set of suspected leakage points based on clustering the time series characteristics and single component characteristics of each inspection data in each inspection cycle;

[0133] A third clustering data unit 23 is configured to determine a third set of suspected leakage points based on clustering features between at least two components of each inspection data in each inspection cycle;

[0134] The fixed interference elimination unit 24 is used to compare the inspection data according to the timing characteristics, location characteristics and component characteristics of each suspected leakage point set, determine the suspected fixed interference source, and update the periodic inspection data for the first time according to the suspected fixed interference source.

[0135] like Figure 3 As shown, in one embodiment of the present invention, the interference data elimination module 20 further includes:

[0136] A first trend comparison unit 25 is used to quantify the linear trend of the change in the inspection vehicle speed and the change in the concentration of a single harmful component in the inspection data within a single inspection cycle;

[0137] The second trend comparison unit 26 is used to quantify the linear trend of the change in the inspection vehicle speed and the change in the concentration ratio of the harmful components in the inspection data within a single inspection cycle;

[0138] A third trend comparison unit 27 is used to quantify the linear trend of the inspection direction change and the fan-shaped area direction change in the inspection data within a single inspection cycle;

[0139] The mobile interference elimination unit 28 is used to determine the suspected mobile interference source according to the degree of adaptation between the inspection data and the inspection vehicle speed, and update the periodic inspection data for the second time according to the suspected mobile interference source.

[0140] like Figure 3 As shown, in one embodiment of the present invention, the suspected point determination module 30 includes:

[0141] The leakage type filtering unit 31 is used to determine the candidate sector areas of the same type as the suspected leakage point according to the methane-ethane concentration ratio in the periodic inspection data;

[0142] A leakage direction determination unit 32 is configured to cluster pointing directions according to the directions of the same type of candidate fan-shaped areas to form a reference direction of a suspected leakage point;

[0143] The leakage range determination unit 33 is configured to form a reference range of the suspected leakage point according to the area of ​​the candidate fan-shaped area forming the reference direction of the suspected leakage point;

[0144] The leaking pipeline determining unit 34 is configured to determine a suspected leaking point of the underground gas pipeline resource according to a reference range.

[0145] The above description is merely a preferred embodiment of the present invention, but the scope of protection of the present invention 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 invention should be included within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be based on the scope of protection of the claims.

Claims

1. A suspected leak point analysis method, characterized in that: include: Generate periodic inspection data within a certain range on the gas pipeline extension path based on the time series dimension and the coordinate dimension; Determine the interference source type based on the time sequence correlation of periodic inspection data and exclude the inspection data of the corresponding interference source to form inspection data update; Determine the suspected leak source based on the spatial correlation of periodic inspection data, and determine the leak point based on the inspection data of the suspected leak source; The periodic inspection data within a certain range on the gas pipeline extension path is formed as follows: Determine the fixed inspection range within the continuous inspection cycle, and form the inspection driving coefficient based on the gas pipeline extension path, meteorological wind speed and extension path wind environment; During the inspection process, adjust the vehicle speed according to the inspection driving coefficient; Generating periodic inspection data based on the inspection data generated at the controlled vehicle speed; The inspection data formed by excluding the corresponding interference source to update the inspection data includes: The first part of the suspected leakage point set is determined by clustering the time series characteristics and road location characteristics of each inspection data in each inspection cycle; Determine a second set of suspected leakage points based on clustering the time series characteristics and single component characteristics of each inspection data in each inspection cycle; Determine a third set of suspected leakage points based on clustering features between at least two components of each inspection data in each inspection cycle; The inspection data is compared based on the timing characteristics, location characteristics and component characteristics of each suspected leakage point set to determine the suspected fixed interference source, and the periodic inspection data is updated for the first time based on the suspected fixed interference source.

2. The suspected leakage point analysis method according to claim 1, characterized in that: The rules for determining suspected fixed interference sources include: - Based on the time information and road location of each inspection data in the suspected leakage point set, combined with GIS resources, the suspected fixed interference source is determined to be a ground gas filling station or underground biogas tank or reservoir near the cluster location; - Based on the two-component ratio information and time information of each inspection data in the suspected leakage point set, combined with the location and GIS resources, the suspected fixed interference source is determined to be a nearby ground gas filling station or underground biogas pool or storage; -Based on the single component information and road location in the suspected leakage point set, combined with GIS resources, the suspected fixed interference source is determined to be a polluted low-lying water source near the cluster location; -Based on the single component concentration information, time information and location information of each inspection data in the suspected leakage point set, combined with GIS resources, the suspected fixed interference source is determined to be a polluted low-lying water source near the cluster location.

3. The suspected leakage point analysis method according to claim 1, characterized in that: Also includes: Quantify the linear trend of changes in inspection vehicle speed and concentration of a single harmful component in inspection data within a single inspection cycle; Quantify the linear trend of the change in inspection vehicle speed and the concentration ratio of harmful components in the inspection data within a single inspection cycle; Quantify the linear trend of inspection direction changes and sector area direction changes in inspection data within a single inspection cycle; The suspected mobile interference source is determined based on the degree of adaptation between the inspection data and the inspection vehicle speed, and the periodic inspection data is updated for the second time based on the suspected mobile interference source.

4. The suspected leakage point analysis method according to claim 3, characterized in that: The rules for determining suspected mobile interference sources include: -Based on the changes in composition and concentration in the inspection data before and after the inspection vehicle speed reaches zero in a single inspection cycle, the suspected mobile interference source is determined to be a moving vehicle that changes its synchronous driving; - Determine whether the suspected mobile interference source is a side-by-side or leading moving vehicle based on the degree of match between the position interval of inspection data with the same concentration of individual harmful components in a single inspection cycle and the speed of the inspection vehicle; - Determine the suspected mobile interference source as a side-by-side or leading moving vehicle based on the degree of match between the position interval of inspection data with the same ratio of concentrations of the same harmful components in a single inspection cycle and the speed of the inspection vehicle; - According to the change of the direction of the fan-shaped area in the inspection data in a single inspection cycle with the speed direction of the inspection vehicle, it is determined that the suspected mobile interference source is a synchronously moving vehicle.

5. The suspected leakage point analysis method according to claim 2, characterized in that: Determining the suspected leakage source based on the spatial correlation of the periodic inspection data and determining the leakage point based on the inspection data of the suspected leakage source includes: Determine the same type of alternative sector areas of the suspected leakage point based on the methane-ethane concentration ratio in the periodic inspection data; Cluster the pointing directions according to the directions of the same type of alternative fan-shaped areas to form the reference directions of the suspected leakage points; Forming a reference range of the suspected leakage point according to the area of ​​the candidate fan-shaped area forming the reference direction of the suspected leakage point; Determine the suspected leakage points of underground gas pipeline resources based on the reference range.

6. A suspected leak point analysis device, characterized in that: include: A memory for storing program codes in a process of processing the suspected leak point analysis method according to any one of claims 1 to 5; A processor is configured to execute the program code.

7. A suspected leak point analysis device, characterized in that: include: An inspection data matching module is used to generate periodic inspection data within a certain range on the gas pipeline extension path according to the time series dimension and the coordinate dimension; Interference data exclusion module, used to determine the type of interference source according to the time sequence correlation of periodic inspection data and exclude the inspection data of the corresponding interference source to form inspection data update; A suspected point determination module is used to determine the suspected leakage source based on the spatial correlation of the periodic inspection data, and to determine the leakage point based on the inspection data of the suspected leakage source; The inspection data matching module includes: An adjustment setting unit is used to determine a fixed inspection range within a continuous inspection cycle, and to form an inspection driving coefficient according to the gas pipeline extension path, meteorological wind speed, and wind environment of the extension path; An adjustment control unit is used to adjust the vehicle speed during the inspection according to the inspection driving coefficient; A data integration unit, used for generating periodic inspection data based on the inspection data generated at the controlled vehicle speed; The interference data elimination module includes: A first clustering data unit is used to determine a first set of suspected leakage points based on clustering time series characteristics and road location characteristics of each inspection data in each inspection cycle; A second clustering data unit is used to determine a second set of suspected leakage points based on clustering the time series characteristics and single component characteristics of each inspection data in each inspection cycle; A third clustering data unit is configured to determine a third set of suspected leakage points based on clustering features between at least two components of each inspection data in each inspection cycle; The fixed interference elimination unit is used to compare the inspection data according to the timing characteristics, location characteristics and component characteristics of each suspected leakage point set, determine the suspected fixed interference source, and update the periodic inspection data for the first time based on the suspected fixed interference source.

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