Pipe network inspection and management method and system based on SAR satellite detection data

Abstract

The present invention belongs to the technical field of pipeline network inspection, and provides a pipeline network inspection management method and system based on SAR satellite detection data, including: regularly observing the water supply pipeline network area through SAR satellite remote sensing images to obtain key distribution values, avoiding misjudgment of suspected water leakage sub-areas due to the interference of uneven soil distribution in the observed sub-areas, improving the recognition accuracy of suspected water leakage sub-areas. Based on the suspected water leakage sub-areas, overlay processing is carried out in combination with the underground pipeline GIS map to draw an artificial leak detection navigation map, plan a simulated leak detection path, and conduct a simulated leak detection test to evaluate the detection effectiveness according to the simulated leak detection path. If the effectiveness is low, local re-adjustment of the path within the leak detection path to be adjusted is identified to obtain an effective leak detection path, which not only avoids blind adjustment of the entire path and improves the probability of detecting the true water leakage point, but also solves the problems of easy repeated inspection and missed inspection in manual inspection.

Description

Technical Field

[0001] The present invention belongs to the technical field of pipeline network inspection, and specifically relates to a pipeline network inspection management method and system based on SAR satellite detection data. Background Art

[0002] As an important part of urban infrastructure, the safe and stable operation of the water supply pipeline network is crucial for the normal operation of the city and the lives of residents. However, pipeline leakage problems occur from time to time, which not only cause waste of water resources, but also may lead to potential safety hazards such as ground collapse.

[0003] In the prior art, one type completely relies on manual census and blind inspection. Although this method has a low construction cost, the manual inspection workload is too large, making it difficult to detect long-term leakage in a short time. Another type of method is to divide independent metering areas (DMA), install some metering instruments and valves in the area, and preliminarily judge whether there is a suspected leakage problem in the area by observing the minimum flow at night. For suspected leakage areas, manual inspections are combined to confirm and accurately locate the leakage points. However, it is difficult to distinguish between normal water use, apparent water use, and real leakage at night. Moreover, the number of leakage areas obtained by SAR satellites is too large and the area is too large, making it easy to have problems of repeated inspections and missed inspections during manual inspections.

[0004] Therefore, in this application: Regular observations are made on the water supply pipeline network area through SAR satellite remote sensing images to obtain key distribution values, so as to be able to reflect which local sub-areas in the observed sub-area are relatively concentrated or dispersed, avoiding misjudgment of suspected leakage sub-areas due to the uneven distribution of soil in the observed sub-area, improving the recognition accuracy of suspected leakage sub-areas, and more accurately identifying suspected leakage sub-areas. Based on the suspected leakage sub-areas, overlay processing is carried out in combination with the underground pipeline GIS map to draw an artificial leak detection navigation map, plan a simulated leak detection path, and conduct a simulated leak detection test to evaluate the effectiveness of detecting artificial suspected leakage based on the simulated leak detection path. If the effectiveness is low, then identify and locally readjust the path within the leak detection path to be adjusted, and conduct re-planning and adjustment to obtain an effective leak detection path, which not only avoids blind adjustment of the entire path, improves the probability of detecting the real leakage point, provides a guarantee for timely repair of leakage problems, but also solves the problems of repeated inspections and missed inspections that are prone to occur during manual inspections.

[0005] For this reason, the present invention provides a pipeline network inspection management method and system based on SAR satellite detection data. Summary of the Invention

[0006] In order to make up for the deficiencies of the prior art and solve at least one of the technical problems proposed in the background art.

[0007] The technical solution adopted by the present invention to solve its technical problems is:

[0008] In the first aspect, a pipeline inspection and management method based on SAR satellite detection data includes:

[0009] Regularly observe the water supply pipeline network area through SAR satellite remote sensing images, and identify suspected leakage sub-areas;

[0010] According to the suspected leakage sub-areas and the water supply pipeline network area, draw a vector map of the suspected leakage area, and perform overlay processing in combination with the underground pipeline GIS map to draw an artificial leak detection navigation map;

[0011] Based on the artificial leak detection navigation map, plan a simulated leak detection path, and conduct a simulated leak detection test to evaluate the detection effectiveness of artificial suspected leaks;

[0012] If the effectiveness is low, identify and locally re-adjust the path within the leakage detection path to be adjusted to obtain an effective leakage detection path.

[0013] As a technical solution of the present invention: The process of identifying suspected leakage sub-areas is as follows:

[0014] Divide the water supply pipeline network area into grids to obtain a number of observation sub-areas;

[0015] Obtain the backscattering coefficient corresponding to each pixel in the observation sub-area, and identify suspected leakage points;

[0016] Process the position coordinates of the suspected leakage points through the Euclidean distance formula, output the key distribution value, and if it is greater than the key distribution threshold, record it as a suspected leakage sub-area.

[0017] As a technical solution of the present invention: The process of drawing a vector map of the suspected leakage area is as follows:

[0018] Arbitrarily select a suspected leakage sub-area, extract all corresponding edge coordinates, and obtain the center point coordinates through the centroid algorithm of the irregular shape area;

[0019] Combine any edge coordinate with the center point coordinate, and obtain the suspected radius through the coordinate distance formula, and select the largest suspected radius as the circumscribed circle radius;

[0020] Based on the center point coordinates and the circumscribed circle radius, perform an operation of circumscribing all suspected leakage sub-areas with a circumscribed circle to obtain a vector map of the suspected leakage area.

[0021] As a technical solution of the present invention: The process of obtaining the edge trend difference in combination with the underground pipeline GIS map is as follows:

[0022] Extract all the feature point coordinates of the underground pipeline GIS map, and connect them respectively to obtain the feature edge to be overlaid;

[0023] Extract the edge coordinates corresponding to all suspected leakage sub - regions within the vector map of the suspected leakage area, and connect them to obtain the reference feature edge;

[0024] Arbitrarily combine the edge of the feature to be superimposed with the reference feature edge, and respectively extract the starting coordinates and ending coordinates of the edge of the feature to be superimposed and the reference feature edge. After processing through the slope calculation formula, perform a difference process and take the absolute value to obtain the edge trend difference.

[0025] As a technical solution of the present invention: in combination with the underground pipeline GIS map, the process of obtaining the edge degree difference is as follows:

[0026] Respectively extract all point coordinates corresponding to the edge of the feature to be superimposed and the reference feature edge, and arbitrarily combine the point coordinates of the edge of the feature to be superimposed with the point coordinates of the reference feature edge to obtain multiple edge degree analysis groups, and obtain the edge degree difference through the Euclidean distance formula.

[0027] As a technical solution of the present invention: the process of drawing the manual leak detection navigation map is as follows:

[0028] Input the edge trend difference and the edge degree difference into the geometric product method respectively, and output to obtain the superposition matching degree;

[0029] If the superposition matching degree is less than or equal to the superposition matching standard degree, draw the manual leak detection navigation map;

[0030] If the superposition matching degree is greater than the superposition matching standard degree, it is also necessary to perform iterative combined analysis on the edge of the feature to be superimposed and other reference feature edges until the superposition matching degree is less than or equal to the superposition matching standard degree, and then draw the manual leak detection navigation map.

[0031] As a technical solution of the present invention: plan the simulated leak detection path and perform simulated leak detection tests, and the process is as follows:

[0032] In the manual leak detection navigation map, plan multiple simulated leak detection paths according to the Chinese postman algorithm;

[0033] Arbitrarily select a simulated leak detection path, extract the suspected leakage sub - regions, and intercept the local simulated path that intersects with the simulated leak detection path;

[0034] Respectively extract all point coordinates of the suspected leakage sub - regions and the local simulated path in the manual leak detection navigation map, perform mean - value processing after processing through the Euclidean distance formula, and calculate the proportion of the total length of the simulated leak detection path occupied to obtain the simulated distance evaluation value;

[0035] Mark the closed area formed between the local simulation path and the suspected water leakage sub-region as the simulation test area, and count the ratio of the number of suspected water leakage points to the total number of all suspected water leakage points in the suspected water leakage sub-region, and perform averaging processing to obtain the simulation ratio evaluation value.

[0036] The technical solution of the present invention is: to evaluate the detection effectiveness of artificial suspected water leakage based on the simulated leak detection path, and the process is as follows:

[0037] Calculate the ratio of the simulation ratio evaluation value to the simulation distance evaluation value to obtain the detection effectiveness value. If the detection effectiveness value is less than or equal to the detection effectiveness threshold, it is recorded as the leak detection path to be adjusted.

[0038] The technical solution of the present invention is: identify the local re-adjustment paths within the leak detection path to be adjusted, and perform re-planning and adjustment to obtain an effective leak detection path. The process is as follows:

[0039] Extract multiple local simulation paths within the leak detection path to be adjusted and process them to obtain the local evaluation value. If the local evaluation value is less than or equal to the local evaluation threshold, it is marked as the local re-adjustment path;

[0040] Based on the starting point and the ending point of the local re-adjustment path, perform iterative fitting through the least squares method to obtain the corresponding local evaluation value, and calculate the difference from the local evaluation threshold. Select the local re-adjustment path with the largest difference, and combine it with other local simulation paths to draw an effective leak detection path.

[0041] In the second aspect, a pipe network inspection and management system based on SAR satellite detection data includes:

[0042] Suspected water leakage identification module: Regularly observe the water supply pipe network area through SAR satellite remote sensing images, and identify the suspected water leakage sub-regions;

[0043] Overlay processing and drawing module: Draw a vector map of the suspected water leakage area according to the suspected water leakage sub-region and the water supply pipe network area, and perform overlay processing in combination with the underground pipeline GIS map to draw an artificial leak detection navigation map;

[0044] Detection effectiveness evaluation module: Based on the artificial leak detection navigation map, plan a simulated leak detection path and perform simulated leak detection tests to evaluate the detection effectiveness of artificial suspected water leakage;

[0045] Local identification and adjustment module: If the effectiveness is low, identify the local re-adjustment paths within the leak detection path to be adjusted to obtain an effective leak detection path.

[0046] The beneficial effects of the present invention are as follows:

[0047] 1. The present invention regularly observes the water supply pipe network area through SAR satellite remote sensing images to obtain key distribution values, so as to reflect which local sub-areas in the observed sub-area are relatively concentrated or dispersed, avoiding misjudgment of suspected leakage sub-areas due to the interference of uneven soil distribution in the observed sub-area, improving the recognition accuracy of suspected leakage sub-areas, accurately identifying suspected leakage sub-areas, drawing a vector map of the suspected leakage area based on the suspected leakage sub-area and the water supply pipe network area, and performing overlay processing in combination with the underground pipeline GIS map to obtain the overlay matching degree, which helps to improve the accuracy and drawing efficiency of the manual leak detection navigation map when combining and overlaying the vector map of the suspected leakage area with the underground pipeline GIS map, and ultimately provides strong support for generating an accurate manual leak detection navigation map;

[0048] 2. Based on the manual leak detection navigation map, the present invention plans and simulates the leak detection path, and conducts a simulated leak detection test to evaluate the detection effectiveness of artificial suspected leaks, so as to clearly understand the proximity of each suspected leak point to the simulated leak detection path, providing a quantitative basis for judging whether the path can effectively cover the suspected leak point, quantifying the coverage degree of the simulated leak detection path for the suspected leakage area, helping to evaluate the rationality and effectiveness of the path, providing data support for subsequent path optimization. If the effectiveness is low, the local path that needs to be readjusted is found, which not only avoids blind adjustment of the entire path, improves the probability of detecting the real leak point, provides guarantee for timely repair of the leak problem, but also solves the problems of repeated inspection and missed inspection that are prone to occur in manual inspection. BRIEF DESCRIPTION OF THE DRAWINGS

[0049] The present invention will be further described below with reference to the accompanying drawings.

[0050] Figure 1 is a flowchart of the steps of the pipe network inspection and management method based on SAR satellite detection data of the present invention;

[0051] Figure 2 is a schematic diagram of the pipe network inspection and management system based on SAR satellite detection data of the present invention. DETAILED DESCRIPTION OF THE INVENTION

[0052] In order to make the technical means, creative features, achieved purposes and effects of the present invention easy to understand, the present invention will be further described below in conjunction with specific embodiments.

[0053] Embodiment 1

[0054] Please refer to Figure 1 As shown, the pipe network inspection and management method based on SAR satellite detection data described in the embodiment of the present invention includes the following steps:

[0055] Step 1: Regularly observe the water supply pipe network area through SAR satellite remote sensing images and identify suspected leakage sub-areas;

[0056] It can be understood that the period of regular observation can be 7 days, 15 days or 30 days;

[0057] In a preferred embodiment, the water supply pipe network area is divided into grids to obtain a number of observation sub-areas with equal areas;

[0058] The process of observing leakage in any observation sub-area through SAR satellite remote sensing images is as follows:

[0059] Exemplarily, obtain the observation image corresponding to any observation sub-area. Taking ENVI as an example, extract each pixel of the observation image to obtain the corresponding backscattering coefficient;

[0060] It can be understood that by extracting the pixels of the observation image of the observation sub-area through SAR satellite remote sensing images and analyzing the backscattering coefficient corresponding to each pixel, the soil moisture content is reflected, so as to initially understand whether there is a preliminary suspected leakage in the observation sub-area;

[0061] Compare the backscattering coefficient with the backscattering standard coefficient, and the process is as follows:

[0062] If the backscattering coefficient is greater than the backscattering standard coefficient, it means that the backscattering coefficient is abnormal, generate a coefficient abnormal signal, and mark the pixel point corresponding to the generated coefficient abnormal signal as a suspected leakage point;

[0063] If the late scattering coefficient is less than or equal to the backscattering standard coefficient, it means that the soil moisture content is normal, and generate a coefficient normal signal;

[0064] Mark the pixel corresponding to the generated coefficient abnormal signal as a suspected leakage point and extract the corresponding position coordinates;

[0065] Combine the position coordinates of any two suspected leakage points to obtain multiple key coordinate groups;

[0066] Input multiple key coordinate groups into the Euclidean distance formula and output to obtain the key distribution value;

[0067] Specifically, the Euclidean distance formula is: , where, represents the total number of key coordinate groups, ( , ) represents the coordinates of one of the key analysis pixels in the th key coordinate group, ( , ) represents the The coordinates of another key analysis pixel within a key coordinate group;

[0068] It should be noted that the purpose of obtaining the key distribution value using the Euclidean distance formula is as follows: Analyzing from the backscattering coefficient of a single pixel is vulnerable to the interference of uneven soil distribution within the observed sub-region, resulting in misjudgment. By obtaining the key distribution value through the Euclidean distance formula, it can reflect which local sub-regions within the observed sub-region are relatively concentrated or dispersed. And the suspected water leakage sub-regions often show a certain degree of aggregation. Therefore, it avoids misjudgment of the suspected water leakage sub-regions and improves the recognition accuracy of the suspected water leakage sub-regions.

[0069] Compare the key distribution value with the key distribution threshold. If the key distribution value is greater than the key distribution threshold, it indicates that the suspected water leakage points within the observed sub-region are relatively concentrated, and it is marked as a suspected water leakage sub-region;

[0070] If the key distribution value is less than or equal to the key distribution threshold, it indicates that the suspected water leakage points within the observed sub-region are less concentrated, and it is marked as a non-suspected water leakage sub-region;

[0071] Step 2: According to the suspected water leakage sub-region and the water supply pipe network region, draw a vector map of the suspected water leakage area, and perform overlay processing in combination with the underground pipeline GIS map to draw an artificial leak detection navigation map;

[0072] It should be noted that the suspected water leakage sub-region is a sub-region with an irregular shape;

[0073] In a preferred embodiment, the process of constructing a vector map of the suspected water leakage area is as follows:

[0074] Arbitrarily select a suspected water leakage sub-region, extract all corresponding edge coordinates, and obtain the center point coordinates through the centroid algorithm for an irregular shape area, the process is as follows:

[0075] A1. Extract the X-axis coordinates within all the edge coordinates, and through the formula: , output to obtain the X coordinate of the center point;

[0076] A2. Extract the Y-axis coordinates within all the edge coordinates, and through the formula: , output to obtain the Y coordinate of the center point;

[0077] Specifically, represents the total number of upper edge coordinates of the suspected water leakage sub-region, ( , ) represents the th edge coordinate on the upper part of the suspected water leakage sub-region;

[0078] A3. Take ( , ) as the center point coordinates;

[0079] Combine any edge coordinates with the coordinates of the center points of the suspected water leakage sub-areas to obtain multiple suspected groups of circumradius;

[0080] Within any suspected group of circumradius, obtain the suspected radius through the coordinate distance formula, compare the sizes of all suspected radii, and select the largest suspected radius as the circumradius;

[0081] Based on the coordinates of the center points corresponding to the suspected water leakage sub-areas and the circumradius, perform an operation of framing the circumcircles for all suspected water leakage sub-areas to obtain a vector map of the suspected water leakage area within the water supply pipe network area;

[0082] It should be noted that by using the centroid algorithm for irregular-shaped areas, the coordinates of the center points are obtained, and a vector map of the suspected water leakage area is constructed. Its functions are as follows:

[0083] Function 1: From the perspective of positioning and marking, by determining the coordinates of the center points, compared with directly using the irregular original water leakage area, it is easier to perform clear marking and identification on the map, which helps to quickly focus on the suspected water leakage sub-areas and improve the marking accuracy of the suspected water leakage sub-areas;

[0084] Function 2: From the perspective of later path inspection planning, based on the coordinates of the center points and the circumradius, it is beneficial to plan a reasonable inspection path for the inspection personnel to improve the inspection efficiency of the inspection personnel;

[0085] Process the underground pipeline GIS map through the boundary tracking method. The specific processing process is as follows:

[0086] Divide the water supply pipe network into several sub-pipelines according to each straight pipeline section to obtain the underground pipeline GIS map;

[0087] It should be noted that if it is the same straight pipeline, but the pipelines with different pipe diameters, or different materials, or different burial depths, or different pipeline construction years, they shall be divided separately as a sub-pipeline;

[0088] Combine and overlay the vector map of the suspected water leakage area with the underground pipeline GIS map to obtain an artificial leak detection navigation map. The process is as follows:

[0089] Perform feature edge processing on the underground pipeline GIS map through the boundary tracking method, extract the corresponding feature point coordinates, and connect all the feature point coordinates to obtain multiple feature edges to be overlaid;

[0090] Based on the vector map of the suspected water leakage area, extract the edge coordinates corresponding to all the suspected water leakage sub-areas within the vector map of the suspected water leakage area and connect them to obtain the reference feature edge;

[0091] Arbitrarily combine the edges of the feature to be superimposed with the edges of the reference feature to obtain multiple groups of feature edge comparisons;

[0092] Within each group of feature edge comparisons, respectively extract the starting coordinates and ending coordinates of the edges of the feature to be superimposed and the reference feature;

[0093] Calculate the starting coordinates and ending coordinates corresponding to the edges of the feature to be superimposed through the slope calculation formula to obtain the trend value of the feature to be superimposed;

[0094] Similarly, calculate the starting coordinates and ending coordinates of the reference feature edge through the slope calculation formula to obtain the reference feature trend value;

[0095] Perform a difference process on the trend value of the feature to be superimposed and the trend value of the reference feature, and take the absolute value to obtain the edge trend difference;

[0096] Respectively extract all the point coordinates corresponding to the edges of the feature to be superimposed and the reference feature, and arbitrarily combine the point coordinates of the edges of the feature to be superimposed with the point coordinates of the reference feature edge to obtain multiple groups of edge degree analysis;

[0097] It should be noted that arbitrarily combining the point coordinates of the edges of the feature to be superimposed with the point coordinates of the reference feature edge, the specific combination rule is: combine in the order from the starting point to the ending point of the edges of the feature to be superimposed and the reference feature;

[0098] For example: combine the starting coordinates of the edges of the feature to be superimposed with the starting coordinates of the reference feature edge into a group of edge degree analysis, and combine the ending coordinates of the edges of the feature to be superimposed with the ending coordinates of the reference feature edge into a group of edge degree analysis;

[0099] Perform edge difference degree processing on multiple groups of edge degree analysis through the Euclidean distance formula, and output to obtain the edge degree difference ;

[0100] Specifically, the Euclidean distance formula is: , where, represents the total number of groups of edge degree analysis, ( , ) represents the point coordinates of the reference feature edge within the th group of edge degree analysis, ( , ) represents the point coordinates of the edges of the feature to be superimposed within the th group of edge degree analysis;

[0101] It can be understood that obtaining the edge degree difference through the Euclidean distance formula, its function lies in:

[0102] Function 1: Quantify the distance difference between points on two feature edges, so as to accurately reflect the degree of deviation in their positions, and provide an accurate quantitative index for evaluating the similarity of two feature edges;

[0103] Function 2: It can provide key information for judging the combined superposition effect of the vector map of the suspected water leakage area and the GIS map of underground pipelines, and more accurately determine which parts of the vector map of the suspected water leakage area and the GIS map of underground pipelines can be well matched and which parts have large differences, thereby improving the accuracy of the superposition processing, and ultimately providing strong support for generating accurate manual leak detection navigation maps;

[0104] The edge trend difference and edge degree difference are input into the geometric product method respectively, and the output is the superposition matching degree;

[0105] It can be understood that the meaning of the overlay matching degree is: it is used to measure the matching degree between the characteristic edges of the suspected water leakage area vector map and the underground pipeline GIS map. Specifically, if the overlay matching degree is small, it means that the difference between the characteristic edge to be overlaid in the edge degree analysis group and the benchmark characteristic edge in edge trend and edge coordinate point is small. If the overlay matching degree is large, it means that the difference between the characteristic edge to be overlaid in the edge degree analysis group and the benchmark characteristic edge in edge trend and edge coordinate point is large, which is helpful to improve the accuracy and efficiency of drawing the manual leak detection navigation map when combining the suspected water leakage area vector map with the underground pipeline GIS map for overlay processing;

[0106] If the overlay match is compared with the overlay match standard, the process is as follows:

[0107] If the overlay matching degree is less than or equal to the overlay matching standard degree, it means that the difference between the edge trend and edge coordinate points of the feature edge to be overlaid in the edge degree analysis group and the benchmark feature edge is small, and the overlay operation is performed to draw the manual leak detection navigation map;

[0108] If the overlay matching degree is greater than the overlay matching standard degree, it means that the edge trend and edge coordinate point differences between the feature edge to be overlaid and the reference feature edge in the edge degree analysis group are large. It is also necessary to iteratively combine and analyze the feature edge to be overlaid with other reference feature edges until the overlay matching degree is less than or equal to the overlay matching standard degree, and then draw the manual leak detection navigation map;

[0109] The specific implementation plan of this embodiment is as follows: Regularly observe the water supply pipe network area through SAR satellite remote sensing images to obtain key distribution values, so as to reflect which local sub-areas in the observed sub-area are more concentrated or more dispersed, avoid misjudgment of suspected water leakage sub-areas due to the interference of uneven soil distribution in the observed sub-area, improve the recognition accuracy of suspected water leakage sub-areas, accurately identify suspected water leakage sub-areas, draw a vector map of the suspected water leakage area according to the suspected water leakage sub-area and the water supply pipe network area, and perform overlay processing in combination with the underground pipeline GIS map to obtain the overlay matching degree, which helps to improve the accuracy and drawing efficiency of the manual leak detection navigation map when combining and overlaying the vector map of the suspected water leakage area with the underground pipeline GIS map, and finally provides strong support for generating an accurate manual leak detection navigation map.

[0110] Embodiment 2

[0111] Please refer to Figure 1 As shown, the pipe network inspection and management method based on SAR satellite detection data described in the embodiment of the present invention further includes the following steps:

[0112] Step 3: Based on the manual leak detection navigation map, plan a simulated leak detection path and conduct a simulated leak detection test to evaluate the effectiveness of detecting artificial suspected water leakage according to the simulated leak detection path;

[0113] In a preferred embodiment, in the manual leak detection navigation map, multiple simulated leak detection paths are planned according to the Chinese postman algorithm;

[0114] Arbitrarily select a simulated leak detection path;

[0115] Extract all suspected water leakage sub-areas in the manual leak detection navigation map;

[0116] Arbitrarily select a suspected water leakage sub-area and intercept the local simulated path intersecting with the simulated leak detection path;

[0117] Extract the coordinates of all suspected water leakage points in the suspected water leakage sub-area and the coordinates of all points of the local simulated path in the manual leak detection navigation map, process them through the Euclidean distance formula, and calculate the ratio with the total length of the simulated leak detection path to obtain the simulated test distance;

[0118] Average the simulated test distances corresponding to all local simulated paths and output the simulated distance evaluation value;

[0119] Specifically, the reason for processing through the Euclidean distance formula is that in the leak detection work, it is crucial to determine the distance between the suspected water leakage point and the simulated leak detection path;

[0120] The functions are as follows: Function 1: From the perspective of precise positioning and distance quantification, it can clearly understand the proximity of each suspected water leakage point to the simulated leakage detection path, providing a quantitative basis for judging whether the path can effectively cover the suspected water leakage point;

[0121] Function 2: From the perspective of simulation testing and effect evaluation, it comprehensively reflects the relative position relationship and coverage degree between the simulated leakage detection path and the suspected water leakage point, thereby quantifying the detection range coverage degree of the simulated leakage detection path for the suspected water leakage area, helping to evaluate the rationality and effectiveness of the path, and providing data support for subsequent path optimization;

[0122] Mark the closed area formed between the local simulation path and the suspected water leakage sub - area as the simulation test area;

[0123] Count the number of suspected water leakage points in the simulation test area, calculate the ratio with the total number of all suspected water leakage points in the suspected water leakage sub - area, and output the proportion of suspected water leakage;

[0124] Perform an averaging process on the proportion of suspected water leakage corresponding to all local simulation paths, and output the simulated proportion evaluation value;

[0125] Calculate the ratio of the simulated proportion evaluation value to the simulated distance evaluation value to obtain the detection effectiveness value;

[0126] It can be understood that the meaning represented by the detection effectiveness value is: from the perspective of path planning, the detection effectiveness value can be used as a key indicator to measure the rationality and effectiveness of the simulated leakage detection path, reflecting the overall effect of the simulated leakage detection path when detecting suspected water leakage points, and helping to optimize the simulated leakage detection path;

[0127] Compare the detection effectiveness value with the detection effectiveness threshold, and the process is as follows:

[0128] If the detection effectiveness value is less than or equal to the detection effectiveness threshold, it means that in the simulation test, the analyzed simulated leakage detection path is far from multiple suspected water leakage points in the suspected water leakage sub - area, and it is marked as a leakage detection path to be adjusted;

[0129] If the detection effectiveness value is greater than the detection effectiveness threshold, it means that in the simulation test, the analyzed simulated leakage detection path is close to multiple suspected water leakage points in the suspected water leakage sub - area, and the analyzed simulated leakage detection path is marked as an effective leakage detection path;

[0130] Step 4: If the effectiveness degree is low, identify the local re - adjustment paths within the leakage detection path to be adjusted to obtain an effective leakage detection path, and report the manual leakage detection points;

[0131] In a preferred embodiment, the planning and adjustment of the leakage detection path to be adjusted is as follows:

[0132] Extract multiple local simulation paths within the leak detection path to be adjusted, obtain the corresponding suspected water leakage ratio and simulation test distance, calculate the ratio, and output to obtain a local evaluation value;

[0133] If the local evaluation value is greater than the local evaluation threshold, there is no need to re-plan and adjust the local simulation path;

[0134] If the local evaluation value is less than or equal to the local evaluation threshold, mark it as a locally re-adjusted path;

[0135] Take the end point of the local simulation path before the locally re-adjusted path as the starting point of the locally re-adjusted path, and take the starting point of the local simulation path after the locally re-adjusted path as the end point of the locally re-adjusted path;

[0136] It should be noted that only consider the situation where neither the local simulation path before the locally re-adjusted path nor the local simulation path after the locally re-adjusted path is the locally re-adjusted path;

[0137] Based on the starting point and end point of the locally re-adjusted path, perform iterative fitting through the least squares method, obtain the corresponding local evaluation value, calculate the difference from the local evaluation threshold, select the locally re-adjusted path with the largest difference, and draw an effective leak detection path with other local simulation paths;

[0138] Based on the effective leak detection path, the leak detection personnel report the leak location;

[0139] The specific solution of this embodiment is: based on the manual leak detection navigation map, plan the simulated leak detection path, and conduct simulated leak detection tests to evaluate the detection effectiveness of artificial suspected water leakage, so as to clearly understand the proximity of each suspected water leakage point to the simulated leak detection path, provide a quantitative basis for judging whether the path can effectively cover the suspected water leakage points, quantify the detection range coverage of the simulated leak detection path for the suspected water leakage area, help evaluate the rationality and effectiveness of the path, provide data support for subsequent path optimization. If the effectiveness is low, find the local path that needs to be re-adjusted, which not only avoids blind adjustment of the entire path, improves the probability of detecting the real leak point, provides a guarantee for timely repair of the leak problem, but also solves the problems of repeated inspections and missed inspections that are prone to occur in manual inspections.

[0140] Embodiment 3

[0141] Please refer to Figure 2 As shown, the pipe network inspection and management system based on SAR satellite detection data described in the embodiment of the present invention includes the following modules:

[0142] Suspected water leakage identification module: Regularly observe the water supply pipe network area through SAR satellite remote sensing images, and identify suspected water leakage sub-areas;

[0143] Overlay processing and drawing module: According to the suspected water leakage sub-region and the water supply pipe network region, draw a vector map of the suspected water leakage area, and perform overlay processing in combination with the underground pipeline GIS map to draw a manual leak detection navigation map;

[0144] Detection effectiveness evaluation module: Based on the manual leak detection navigation map, plan a simulated leak detection path, and conduct a simulated leak detection test to evaluate the detection effectiveness of the artificial suspected water leakage;

[0145] Local identification and adjustment module: If the effectiveness is low, identify and locally re-adjust the path within the leak detection path to be adjusted to obtain an effective leak detection path.

[0146] The above shows and describes the basic principles, main features and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited by the above embodiments. The above embodiments and the descriptions in the specification only illustrate the principles of the present invention. Without departing from the spirit and scope of the present invention, the present invention will have various changes and improvements, and these changes and improvements all fall within the scope of the present invention claimed. The scope of protection claimed by the present invention is defined by the appended claims and their equivalents.

Claims

1. A pipeline inspection and management method based on SAR satellite detection data, characterized in that: Including: Regularly observing the water supply pipe network area through SAR satellite remote sensing images and identifying suspected leakage sub-areas; Drawing a vector map of the suspected leakage area based on the suspected leakage sub-areas and the water supply pipe network area, and performing overlay processing in combination with the underground pipeline GIS map to draw an artificial leak detection navigation map; Based on the artificial leak detection navigation map, planning a simulated leak detection path and performing a simulated leak detection test to evaluate the detection effectiveness of artificial suspected leakage; If the effectiveness is low, identify and locally re-adjust the path within the leak detection path to be adjusted to obtain an effective leak detection path; The process of obtaining the artificial leak detection navigation map by performing overlay processing on the vector map of the suspected leakage area and the underground pipeline GIS map is as follows: Extract all the characteristic point coordinates of the underground pipeline GIS map and connect them respectively to obtain the characteristic edge to be overlaid; Extract the edge coordinates corresponding to all the suspected leakage sub-areas within the vector map of the suspected leakage area and connect them to obtain the reference characteristic edge; Arbitrarily combine the characteristic edge to be overlaid with the reference characteristic edge, and respectively extract the starting point coordinates and ending point coordinates of the characteristic edge to be overlaid and the reference characteristic edge. After processing through the slope calculation formula, obtain the characteristic trend value to be overlaid and the reference characteristic trend value respectively, and perform difference processing, take the absolute value to obtain the edge trend difference; Respectively extract all the point coordinates corresponding to the characteristic edge to be overlaid and the reference characteristic edge, and combine them in the order from the starting point to the ending point of the characteristic edge to be overlaid and the reference characteristic edge to obtain multiple edge degree analysis groups, and obtain the edge degree difference through the Euclidean distance formula; Take the product of the edge trend difference and the edge degree difference as the overlay matching degree, and determine whether to draw an artificial leak detection navigation map according to the size of the overlay matching degree.

2. The pipeline inspection and management method based on SAR satellite detection data according to claim 1, characterized in that: The process of identifying the suspected leakage sub-areas is as follows: Divide the water supply pipe network area into grids to obtain several observation sub-areas; Obtain the backscattering coefficient corresponding to each pixel within the observation sub-area and identify the suspected leakage points; Process the position coordinates of the suspected leakage points through the Euclidean distance formula, output and obtain the key distribution value. If it is greater than the key distribution threshold, it is recorded as a suspected leakage sub-area.

3. The pipeline inspection and management method based on SAR satellite detection data according to claim 1, wherein: The process of drawing the vector map of the suspected leakage area is as follows: Arbitrarily select a suspected leakage sub-area, extract all the corresponding edge coordinates, and obtain the center point coordinates through the centroid algorithm of the irregular shape area; Combine any edge coordinates with the center point coordinates, and obtain the suspected radius through the coordinate distance formula, and select the largest suspected radius as the circumcircle radius; Based on the center point coordinates and the circumcircle radius, perform an operation of framing all the suspected leakage sub-areas with circumcircles to obtain the vector map of the suspected leakage area.

4. The pipeline inspection and management method based on SAR satellite detection data according to claim 1, characterized in that: The process of planning a simulated leak detection path and performing a simulated leak detection test is as follows: Within the artificial leak detection navigation map, plan multiple simulated leak detection paths according to the Chinese postman problem algorithm; Arbitrarily select a simulated leak detection path, extract the suspected leakage sub-areas, and intercept the local simulated path that intersects with the simulated leak detection path; Extract the coordinates of all points of the suspected water leakage sub-region and the local simulation path in the manual leak detection navigation map, perform mean value processing after processing through the Euclidean distance formula, calculate the proportion of the total length of the simulated leak detection path, and obtain the simulated distance evaluation value; Mark the closed area formed between the local simulation path and the suspected water leakage sub-region as the simulated test area, and count the ratio of the number of suspected water leakage points to the total number of all suspected water leakage points in the suspected water leakage sub-region, and perform mean value processing to obtain the simulated proportion evaluation value.

5. The pipeline inspection and management method based on SAR satellite detection data according to claim 4, characterized in that: The evaluation is based on the effectiveness of manual detection of suspected water leakage along the simulated leak detection path. The process is as follows: Calculate the ratio of the simulated proportion evaluation value to the simulated distance evaluation value to obtain the detection effective value. If the detection effective value is less than or equal to the detection effective threshold, it is recorded as the leak detection path to be adjusted.

6. The pipeline inspection and management method based on SAR satellite detection data according to claim 1, characterized in that: Identify the local re-adjustment path within the leak detection path to be adjusted, and perform re-planning and adjustment to obtain an effective leak detection path. The process is as follows: Extract multiple local simulation paths within the leak detection path to be adjusted and process them to obtain the local evaluation value. If the local evaluation value is less than or equal to the local evaluation threshold, it is marked as the local re-adjustment path; Based on the starting point and the ending point of the local re-adjustment path, perform iterative fitting through the least squares method to obtain the corresponding local evaluation value, and calculate the difference from the local evaluation threshold. Select the local re-adjustment path with the largest difference, and combine it with other local simulation paths to draw an effective leak detection path.

7. Pipeline inspection management system based on SAR satellite detection data, characterized in that: Including: Suspected water leakage identification module: Regularly observe the water supply pipe network area through SAR satellite remote sensing images, and identify the suspected water leakage sub-region; Overlay processing and drawing module: Draw a vector map of the suspected water leakage area based on the suspected water leakage sub-region and the water supply pipe network area, and perform overlay processing in combination with the underground pipeline GIS map to draw a manual leak detection navigation map; Detection effectiveness evaluation module: Based on the manual leak detection navigation map, plan the simulated leak detection path and conduct simulated leak detection tests to evaluate the effectiveness of manual detection of suspected water leakage; Local identification and adjustment module: If the effectiveness is low, identify the local re-adjustment path within the leak detection path to be adjusted to obtain an effective leak detection path; The process of obtaining the manual leak detection navigation map by performing overlay processing on the vector map of the suspected water leakage area and the underground pipeline GIS map is as follows: Extract the coordinates of all feature points of the underground pipeline GIS map and connect them respectively to obtain the feature edge to be overlaid; Extract the edge coordinates corresponding to all suspected water leakage sub-regions within the vector map of the suspected water leakage area and connect them to obtain the reference feature edge; Arbitrarily combine the feature edge to be overlaid with the reference feature edge, and respectively extract the starting point coordinates and ending point coordinates of the feature edge to be overlaid and the reference feature edge. After processing through the slope calculation formula, obtain the trend value of the feature to be overlaid and the reference feature trend value respectively, and perform difference processing and take the absolute value to obtain the edge trend difference; Extract the coordinates of all points corresponding to the feature edge to be overlaid and the reference feature edge respectively, and combine them in the order from the starting point to the ending point of the feature edge to be overlaid and the reference feature edge to obtain multiple edge degree analysis groups, and obtain the edge degree difference through the Euclidean distance formula; Use the product of the edge trend difference and the edge degree difference as the superposition matching degree, and determine whether to draw an artificial leak detection navigation map according to the magnitude of the superposition matching degree.

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