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

Abstract

The invention belongs to the technical field of pipe network inspection, and provides a pipe network inspection management method and system based on SAR satellite detection data, and the method comprises the steps: carrying out the regular observation of a water supply pipe network region through an SAR satellite remote sensing image, obtaining a key distribution value, avoiding the interference caused by the non-uniform distribution of soil in an observed sub-region, and carrying out the misjudgment of a suspected water leakage sub-region, the method improves the recognition accuracy of the suspected water leakage sub-region, carries out the superposition processing based on the suspected water leakage sub-region and in combination with an underground pipeline GIS map, draws a manual leakage detection navigation map, plans a simulation leakage detection path, carries out the simulation leakage detection test, evaluates the detection effectiveness degree based on the simulation leakage detection path, and carries out the detection of the suspected water leakage sub-region if the effectiveness degree is lower. If yes, a local readjustment path in the to-be-adjusted leakage detection path is identified, an effective leakage detection path is obtained, blind adjustment of the whole path is avoided, the probability of detecting a real water leakage point is improved, and the problems of repeated inspection and inspection omission easily occurring in manual inspection are solved.

Description

Technical Field

[0001] The invention belongs to the technical field of pipe network inspection, and in particular to a pipe 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 water supply pipelines is crucial to the normal operation of the city and the lives of residents. However, water leakage in pipelines occurs from time to time, which not only causes waste of water resources, but also may cause safety hazards such as ground collapse.

[0003] Among the existing technologies, one method completely relies on manual census blind inspection. Although this method has low construction cost, the workload of manual inspection is too large, making it difficult to find long-term water leakage in a short time. Another method is to divide the area into independent metering areas (DMAs), install some metering instruments and valves in the area, and observe the minimum flow at night to preliminarily judge whether there is a suspected water leakage problem in the area. For the suspected water leakage area, combined with manual inspection, it is confirmed and accurately located. However, it is difficult to distinguish between normal water use, apparent water use and real water leakage at night, and the number of water leakage areas obtained by SAR satellites is too large and the area is too large. Manual inspections are prone to repeated inspections and missed inspections. Therefore, the present application: regularly observes the water supply 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-areas are more concentrated or more dispersed, avoid misjudgment of suspected leaking sub-areas due to interference from uneven soil distribution in the observed sub-areas, improve the recognition accuracy of suspected leaking sub-areas, more accurately identify suspected leaking sub-areas, based on the suspected leaking sub-areas, combine with the underground pipeline GIS map for overlay processing, draw a manual leak detection navigation map, plan a simulated leak detection path, and conduct a simulated leak detection test to evaluate the effectiveness of artificial suspected leak detection based on the simulated leak detection path. If the effectiveness is low, identify the local readjustment path within the leak detection path to be adjusted, re-plan and adjust it, and obtain an effective leak detection path. This not only avoids blind adjustment of the entire path, increases the probability of detecting the real leak point, and provides a guarantee for timely repair of the leak problem, but also solves the problem of repeated inspections and missed inspections that are prone to occur in manual inspections.

[0004] To this end, the present invention provides a pipeline network inspection management method and system based on SAR satellite detection data. Summary of the invention

[0005] In order to make up for the deficiencies of the prior art, at least one technical problem raised in the background technology is solved.

[0006] The technical solution adopted by the present invention to solve its technical problem is: First, the pipeline network inspection management method based on SAR satellite detection data includes: Regularly observe the water supply network area through SAR satellite remote sensing images and identify suspected leakage sub-areas; Draw a vector map of the suspected leaking area based on the suspected leaking sub-area and water supply network area, and overlay it with the underground pipeline GIS map to draw a manual leak detection navigation map; Based on the manual leak detection navigation map, plan a simulated leak detection route and conduct a simulated leak detection test to evaluate the effectiveness of manual suspected leak detection; If the effectiveness is low, a local readjustment path within the leak detection path to be adjusted is identified to obtain an effective leak detection path.

[0007] As a technical solution of the present invention, the process of identifying the suspected water leakage sub-area is as follows: Divide the water supply network area into grids to obtain several observation sub-areas; Obtain the backscatter coefficient corresponding to each pixel in the observation sub-area and identify the suspected water leakage point; The position coordinates of the suspected leakage point are processed by the Euclidean distance formula, and the key distribution value is output. If it is greater than the key distribution threshold, it is recorded as a suspected leakage sub-area.

[0008] The technical solution of the present invention is to draw a vector diagram of the suspected water leakage area, and the process is as follows: Randomly select a suspected leaking sub-region, extract all corresponding edge coordinates, and obtain the center point coordinates through the irregular shape region centroid algorithm; Combine any edge coordinates with the center point coordinates, and use the coordinate distance formula to get the suspected radius, and select the largest suspected radius as the circumscribed circle radius; Based on the coordinates of the center point and the radius of the circumscribed circle, all suspected leaking sub-areas are circumscribed to obtain a vector diagram of the suspected leaking area.

[0009] As a technical solution of the present invention, the process of obtaining edge trend difference value by combining underground pipeline GIS map is as follows: Extract the coordinates of all feature points in the underground pipeline GIS map and connect them separately to obtain the feature edges to be superimposed; Extract the edge coordinates corresponding to all suspected water leakage sub-areas in the suspected water leakage area vector map, and connect them to obtain the reference feature edge; The feature edge to be superimposed is arbitrarily combined with the reference feature edge, and the starting point coordinates and the end point coordinates of the feature edge to be superimposed and the reference feature edge are extracted respectively. After being processed by the slope calculation formula, difference processing is performed and the absolute value is taken to obtain the edge trend difference.

[0010] As a technical solution of the present invention, the process of obtaining the edge degree difference value in combination with the underground pipeline GIS map is as follows: The coordinates of all points corresponding to the edge of the feature to be superimposed and the reference feature edge are extracted respectively, and the coordinates of the edge points of the feature to be superimposed are arbitrarily combined with the coordinates of the edge points of the reference feature to obtain multiple edge degree analysis groups, and the edge degree difference is obtained through the Euclidean distance formula.

[0011] As a technical solution of the present invention, the process of drawing a manual leak detection navigation map is as follows: The edge trend difference and edge degree difference are input into the geometric product method respectively, and the output is the superposition matching degree; If the overlay matching degree is less than or equal to the overlay matching standard degree, draw a manual leak detection navigation map; If the overlay matching degree is greater than the overlay matching standard degree, it is necessary to iteratively combine and analyze the feature edges 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 a manual leak detection navigation map.

[0012] The technical solution of the present invention is to plan a simulated leak detection path and perform a simulated leak detection test. The process is as follows: In the manual leak detection navigation map, multiple simulated leak detection routes are planned according to the Chinese Postman algorithm; Randomly select a simulated leak detection path, extract the suspected leak sub-area, and intercept the local simulated path that intersects with the simulated leak detection path; The coordinates of all points in the suspected leak sub-area and the local simulation path in the manual leak detection navigation map are extracted respectively, and the average processing is performed after processing by the Euclidean distance formula. The proportion of the total length of the simulated leak detection path is calculated to obtain the simulation distance evaluation value; The closed area formed by the local simulation path and the suspected leakage sub-area is marked as the simulation test area, and the ratio of the number of suspected leakage points to the total number of all suspected leakage points in the suspected leakage sub-area is counted and averaged to obtain the simulation proportion assessment value.

[0013] As a technical solution of the present invention, the effectiveness of artificial suspected water leakage detection based on the simulated leak detection path is evaluated, and the process is as follows: The ratio of the simulated proportion evaluation value to the simulated distance evaluation value is calculated 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.

[0014] As a technical solution of the present invention, a local readjustment path within the leak detection path to be adjusted is identified, and a replanning and adjustment is performed to obtain an effective leak detection path. The process is as follows: Extract multiple local simulation paths in the leak detection path to be adjusted and process them to obtain a local evaluation value. If the local evaluation value is less than or equal to a local evaluation threshold, it is marked as a local readjustment path; Based on the starting point and end point of the local readjustment path, the least squares method is used for iterative fitting to obtain the corresponding local evaluation value, which is subtracted from the local evaluation threshold. The local readjustment path with the largest difference is selected and combined with other local simulation paths to draw an effective leak detection path.

[0015] Secondly, the pipeline network inspection management system based on SAR satellite detection data includes: Suspected water leakage identification module: Regularly observe the water supply network area through SAR satellite remote sensing images and identify suspected water leakage sub-areas; Overlay processing and drawing module: Draw a vector map of the suspected leaking area based on the suspected leaking sub-area and water supply network area, and overlay it 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 a simulated leak detection route, and conduct a simulated leak detection test to evaluate the effectiveness of manual suspected leak detection; Local identification and adjustment module: If the effectiveness is low, the local re-adjustment path within the leak detection path to be adjusted is identified to obtain an effective leak detection path.

[0016] The beneficial effects of the present invention are as follows: 1. The present invention regularly observes the water supply 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-areas are relatively concentrated or relatively dispersed, avoid misjudgment of suspected leakage sub-areas due to interference from uneven soil distribution in the observed sub-areas, improve the recognition accuracy of suspected leakage sub-areas, more accurately identify suspected leakage sub-areas, draw a vector map of suspected leakage areas according to suspected leakage sub-areas and water supply network areas, and combine with underground pipeline GIS maps for superposition processing to obtain superposition matching degree, so as to help improve the accuracy and efficiency of drawing manual leak detection navigation maps when combining the suspected leakage area vector map with the underground pipeline GIS map for superposition processing, and finally provide strong support for generating accurate manual leak detection navigation maps; 2. The present invention plans a simulated leak detection route based on the manual leak detection navigation map, and conducts simulated leak detection tests to evaluate the effectiveness of artificial suspected leak detection, so as to clearly understand the proximity of each suspected leak point to the simulated leak detection route, and provides a quantitative basis for judging whether the path can effectively cover the suspected leak point. Quantifying the coverage of the detection range of the suspected leak area by the simulated leak detection route helps to evaluate the rationality and effectiveness of the route, and provide data support for subsequent optimization of the route. If the effectiveness is low, the local route that needs to be readjusted is found, which not only avoids blind adjustment of the entire route, but also increases the probability of detecting the real leak point, providing a guarantee for timely repair of the leak problem, but also solves the problem of repeated inspections and missed inspections that are prone to occur during manual inspections. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] The present invention will be further described below in conjunction with the accompanying drawings.

[0018] Figure 1 It is a flow chart of the steps of the pipeline network inspection management method based on SAR satellite detection data of the present invention; Figure 2 It is a schematic diagram of the pipeline network inspection management system based on SAR satellite detection data of the present invention. DETAILED DESCRIPTION

[0019] In order to make the technical means, creative features, objectives and effects achieved by the present invention easy to understand, the present invention is further explained below in conjunction with specific implementation methods.

[0020] Example 1 See also Figure 1 As shown, the pipeline network inspection management method based on SAR satellite detection data described in the embodiment of the present invention includes the following steps: Step 1: Regularly observe the water supply network area through SAR satellite remote sensing images and identify suspected leakage sub-areas; It is understood that the period of regular observations may be 7, 15 or 30 days; In a preferred embodiment, the water supply network area is divided into grids to obtain a number of observation sub-areas of equal area; Water leakage observation is carried out in any observation sub-area through SAR satellite remote sensing images. The specific process is as follows: Exemplarily, an observation image corresponding to any observation sub-area is obtained, and taking ENVI as an example, each pixel of the observation image is extracted to obtain the corresponding backscattering coefficient; It can be understood that the observation images of the observation sub-area are pixel-extracted through SAR satellite remote sensing images, and the backscatter coefficient corresponding to each pixel is analyzed to reflect the soil moisture content, so as to achieve a preliminary understanding of whether there is a preliminary suspected water leakage in the observation sub-area; The backscatter coefficient is compared with the backscatter standard coefficient as follows: If the backscatter coefficient is greater than the standard backscatter coefficient, it means that the backscatter coefficient is abnormal, and a coefficient abnormality signal is generated. The pixel point corresponding to the generated coefficient abnormality signal is recorded as a suspected water leakage point; If the backscatter coefficient is less than or equal to the backscatter standard coefficient, it means that the soil moisture content is normal and the normal coefficient signal is generated; The pixels corresponding to the abnormal signals of the generated coefficients are marked as suspected water leakage points, and the corresponding position coordinates are extracted; Combine the position coordinates of any two suspected water leakage points to obtain multiple key coordinate groups; Input multiple key coordinate groups into the Euclidean distance formula, and output the key distribution value; Specifically, the Euclidean distance formula is: ,in, Expressed as the total number of key coordinate groups, ( , ) is expressed as The coordinates of one of the key analysis pixels in the key coordinate group, ( , ) is expressed as The coordinates of another key analysis pixel in the key coordinate group; It should be noted that the purpose of obtaining the key distribution value by the Euclidean distance formula is that the analysis of the backscattering coefficient of a single pixel is easily disturbed by the uneven distribution of soil in the observation sub-region, resulting in misjudgment. The key distribution value obtained by the Euclidean distance formula can reflect which local sub-regions in the observation sub-region are more concentrated or more dispersed, and the suspected leakage sub-regions often show a certain degree of aggregation. Therefore, the misjudgment of the suspected leakage sub-region is avoided, and the recognition accuracy of the suspected leakage sub-region is improved; Compare the key distribution value with the key distribution threshold. If the key distribution value is greater than the key distribution threshold, it means that the suspected leakage points in the observation sub-area are relatively concentrated and marked as the suspected leakage sub-area; If the key distribution value is less than or equal to the key distribution threshold, it means that the suspected leakage points in the observation sub-area are not concentrated, and it is marked as a non-suspected leakage sub-area; Step 2: Draw a vector map of the suspected leaking area based on the suspected leaking sub-area and water supply network area, and overlay it with the underground pipeline GIS map to draw a manual leak detection navigation map; It should be noted that the suspected leakage sub-area is a sub-area with an irregular shape; In a preferred embodiment, a vector diagram of a suspected water leakage area is constructed, and the specific process is as follows: Randomly select a suspected leaking sub-region, extract all corresponding edge coordinates, and obtain the center point coordinates through the irregular shape region centroid algorithm. The process is as follows: A1, extract the X-axis coordinates of all edge coordinates, and use the formula: , output the X coordinate of the center point; A2, extract the Y-axis coordinates of all edge coordinates, and use the formula: , output the Y coordinate of the center point; In detail, It is expressed as the total number of edge coordinates on the suspected leakage sub-area, ( , ) indicates the suspected leakage sub-area edge coordinates; A3, , ) as the center point coordinates; Combining any edge coordinates with the coordinates of the center point of the suspected leaking sub-region to obtain multiple suspected groups of outer circle radii; In any suspected group of outer circle radius, the suspected radius is obtained by using the coordinate distance formula, and all suspected radii are compared in size, and the largest suspected radius is selected as the circumscribed circle radius; Based on the coordinates of the center point and the radius of the circumscribed circle corresponding to the suspected leakage sub-area, all the suspected leakage sub-areas are circumscribed by a circle, and a vector diagram of the suspected leakage area is obtained in the water supply network area; It should be noted that the center point coordinates are obtained through the irregular shape area centroid algorithm to construct a vector map of the suspected leaking area, which has the following functions: Function 1: From the perspective of positioning and marking, by determining the coordinates of the center point, it is easier to clearly mark and identify on the map than directly using the irregular original leakage area, which helps to quickly focus on the suspected leakage sub-area and improve the accuracy of marking the suspected leakage sub-area; Function 2: From the perspective of later inspection path planning, based on the center point coordinates and the radius of the circumscribed circle, it is helpful to plan a reasonable inspection path for the missed inspection personnel and improve the inspection efficiency of the missed inspection personnel; The underground pipeline GIS map is processed by the boundary tracking method. The specific processing process is as follows: Divide the water supply network into several sub-pipelines according to each straight line to obtain the underground pipeline GIS map; It should be noted that if the pipeline is the same straight line but has different diameters, materials, burial depths, or pipeline construction years, it will be divided separately as a sub-pipeline; Combine and overlay the vector map of the suspected leaking area with the GIS map of underground pipelines to obtain a manual leak detection navigation map. The process is as follows: The feature edge processing of underground pipeline GIS map is carried out by boundary tracking method, the corresponding feature point coordinates are extracted, and all feature point coordinates are connected to obtain multiple feature edges to be superimposed; Taking the vector map of the suspected water leakage area as a reference, extract the edge coordinates corresponding to all the suspected water leakage sub-areas in the vector map of the suspected water leakage area, and connect them to obtain the reference feature edge; Arbitrarily combining the feature edges to be superimposed with the reference feature edges to obtain multiple feature edge comparison groups; In the feature edge comparison group, the starting point coordinates and the ending point coordinates of the feature edge to be superimposed and the reference feature edge are respectively extracted; The starting point coordinates and the end point coordinates corresponding to the edge of the feature to be superimposed are calculated by using the slope calculation formula to obtain the trend value of the feature to be superimposed; Similarly, the starting point coordinates and the end point coordinates of the edge of the reference feature are calculated by the slope calculation formula to obtain the reference feature trend value; Perform difference processing on the characteristic trend value to be superimposed and the benchmark characteristic trend value, and take the absolute value to obtain the edge trend difference; Extract all the point coordinates corresponding to the edge of the feature to be superimposed and the reference feature edge respectively, and arbitrarily combine the coordinates of the edge points of the feature to be superimposed with the coordinates of the edge points of the reference feature to obtain multiple edge degree analysis groups; It should be noted that the coordinates of the edge points of the feature to be superimposed and the coordinates of the edge points of the reference feature are arbitrarily combined, and the specific combination rule is: combining in the order from the starting point to the end point of the edge of the feature to be superimposed and the edge of the reference feature; For example: the starting point coordinates of the edge of the feature to be superimposed and the starting point coordinates of the edge of the reference feature are combined into an edge degree analysis group, and the end point coordinates of the edge of the feature to be superimposed and the end point coordinates of the edge of the reference feature are combined into an edge degree analysis group; The edge difference degree of multiple edge degree analysis groups is processed by the Euclidean distance formula, and the edge degree difference value is output ; Specifically, the Euclidean distance formula is: ,in, Expressed as the total number of marginal degree analysis groups, ( , ) is expressed as The coordinates of the reference feature edge points in the edge degree analysis group, ( , ) is expressed as The coordinates of the feature edge points to be superimposed within the edge degree analysis group; It can be understood that the role of obtaining the edge degree difference through the Euclidean distance formula is: 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; 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; The edge trend difference and edge degree difference are input into the geometric product method respectively, and the output is the superposition matching degree; 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; If the overlay match is compared with the overlay match standard, the process is as follows: 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; 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; The specific implementation plan of this embodiment is: regularly observe the water supply network area through SAR satellite remote sensing images to obtain key distribution values, so as to reflect which local sub-areas in the observation sub-area are more concentrated or more dispersed, avoid misjudgment of suspected leakage sub-areas due to interference from uneven soil distribution in the observation sub-area, improve the recognition accuracy of suspected leakage sub-areas, and more accurately identify suspected leakage sub-areas. Draw a vector map of the suspected leakage area based on the suspected leakage sub-area and the water supply network area, and overlay it with the underground pipeline GIS map to obtain the overlay matching degree, which is helpful to improve the accuracy and efficiency of drawing the manual leak detection navigation map when combining the suspected leakage area vector map with the underground pipeline GIS map for overlay processing, and finally provide strong support for generating accurate manual leak detection navigation maps.

[0021] Example 2 See also Figure 1 As shown, the pipeline network inspection management method based on SAR satellite detection data described in the embodiment of the present invention also includes the following steps: Step 3: Based on the manual leak detection navigation map, plan a simulated leak detection route and conduct a simulated leak detection test to evaluate the effectiveness of artificial suspected leak detection based on the simulated leak detection route; In a preferred embodiment, in the manual leak detection navigation map, multiple simulated leak detection paths are planned according to the Chinese Postman Algorithm; Select any simulated leak detection path; Extract all suspected leaking sub-areas in the manual leak detection navigation map; Randomly select a suspected leaking sub-area and intercept the local simulation path that intersects with the simulated leak detection path; The coordinates of all suspected leaking points in the suspected leaking sub-area and the coordinates of all points in the local simulation path in the manual leak detection navigation map are extracted, processed using the Euclidean distance formula, and the ratio is calculated with the total length of the simulated leak detection path to obtain the simulated test distance; The simulated test distances corresponding to all local simulated paths are averaged and output to obtain a simulated distance evaluation value; Specifically, the reason for processing by the Euclidean distance formula is that: in leak detection work, it is crucial to determine the distance between the suspected leak point and the simulated leak detection path; The functions are: Function 1: From the perspective of precise positioning and distance quantification, it is possible 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; Function 2: From the perspective of simulation test and effect evaluation, it comprehensively reflects the relative position relationship and coverage between the simulated leak detection path and the suspected leak point, thereby quantifying the coverage of the simulated leak detection path on the suspected leak area, which helps to evaluate the rationality and effectiveness of the path and provide data support for subsequent optimization of the path; Mark the closed area formed between the local simulation path and the suspected leakage sub-area as a simulation test area; Count the number of suspected water leakage points in the simulated test area, and calculate the ratio with the total number of all suspected water leakage points in the suspected water leakage sub-area, and output the suspected water leakage ratio; The suspected leakage proportions corresponding to all local simulation paths are averaged and the simulated proportion evaluation value is output; Calculate the ratio of the simulated proportion evaluation value to the simulated distance evaluation value to obtain the detection effective value; It can be understood that the meaning of the detection effective value is: from the perspective of path planning, the detection effective value can be used as a key indicator to measure the rationality and effectiveness of the simulated leak detection path, reflecting the overall effect of the simulated leak detection path in detecting suspected leaks, and helping to optimize the simulated leak detection path; The detection effective value is compared with the detection effective threshold. The process is as follows: If the detection effective value is less than or equal to the detection effective threshold, it means that the simulated leak detection path being analyzed is far away from multiple suspected leak points in the suspected leak sub-area in the simulation test, and is marked as a leak detection path to be adjusted; If the detection effective value is greater than the detection effective threshold, it means that the analyzed simulated leak detection path is close to multiple suspected leak points in the suspected leak sub-area in the simulation test, and the analyzed simulated leak detection path is marked as a valid leak detection path; Step 4: If the effectiveness is low, identify the local leak detection path to be adjusted and readjust the path to obtain the effective leak detection path, and report the manual leak detection point; In a preferred embodiment, the leak detection path to be adjusted is planned and adjusted, and the process is as follows: Extract multiple local simulation paths within the leak detection path to be adjusted, obtain the corresponding suspected leakage ratio and simulation test distance, perform ratio calculation, and output the local evaluation value; If the local evaluation value is greater than the local evaluation threshold, there is no need to replan and adjust the local simulation path; If the local evaluation value is less than or equal to the local evaluation threshold, it is marked as a local readjustment path; The local simulation path end point before the local readjustment path is taken as the local readjustment path start point, and the local simulation path start point after the local readjustment path is taken as the local readjustment path end point; It should be noted that only the case where the local simulation path before the local re-adjustment path and the local simulation path after the local re-adjustment path are not local re-adjustment paths is considered; Based on the starting point and the end point of the local readjustment path, the least square method is used for iterative fitting to obtain the corresponding local evaluation value, and the difference is made with the local evaluation threshold. The local readjustment path with the largest difference is selected, and it is plotted with other local simulation paths to obtain an effective leak detection path; Based on the effective leak detection path, leak detection personnel report the leak location through the satellite leak detection APP; The specific scheme of this embodiment is: based on the manual leak detection navigation map, a simulated leak detection path is planned, and a simulated leak detection test is performed to evaluate the effectiveness of the detection of artificial suspected leaks, so that the proximity of each suspected leak point to the simulated leak detection path can be clearly understood, and a quantitative basis is provided for judging whether the path can effectively cover the suspected leak point. The coverage of the detection range of the suspected leak area by the quantified simulated leak detection path is helpful to evaluate the rationality and effectiveness of the path, and provide data support for the subsequent optimization of the path. 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, but also increases the probability of detecting the real leak point, providing a guarantee for timely repair of the leak problem, but also solves the problem of repeated inspections and missed inspections that are prone to occur in manual inspections.

[0022] Example 3 See also Figure 2 As shown, the pipeline network inspection management system based on SAR satellite detection data according to the embodiment of the present invention includes the following modules: Suspected water leakage identification module: Regularly observe the water supply network area through SAR satellite remote sensing images and identify suspected water leakage sub-areas; Overlay processing and drawing module: Draw a vector map of the suspected leaking area based on the suspected leaking sub-area and water supply network area, and overlay it 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 a simulated leak detection route, and conduct a simulated leak detection test to evaluate the effectiveness of manual suspected leak detection; Local identification and adjustment module: If the effectiveness is low, the local re-adjustment path within the leak detection path to be adjusted is identified to obtain an effective leak detection path.

[0023] The above shows and describes the basic principles, main features and advantages of the present invention. It should be understood by those skilled in the art that the present invention is not limited to the above embodiments. The above embodiments and descriptions are only for explaining the principles of the present invention. Without departing from the spirit and scope of the present invention, the present invention may have various changes and improvements, which fall within the scope of the present invention. The scope of protection of the present invention is defined by the attached claims and their equivalents.

Claims

1. A pipeline network inspection management method based on SAR satellite detection data, characterized in that: include: Regularly observe the water supply network area through SAR satellite remote sensing images and identify suspected leakage sub-areas; Draw a vector map of the suspected leaking area based on the suspected leaking sub-area and water supply network area, and overlay it with the underground pipeline GIS map to draw a manual leak detection navigation map; Based on the manual leak detection navigation map, plan a simulated leak detection route and conduct a simulated leak detection test to evaluate the effectiveness of manual suspected leak detection; If the effectiveness is low, a local readjustment path within the leak detection path to be adjusted is identified to obtain an effective leak detection path.

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

3. The pipeline network inspection management method based on SAR satellite detection data according to claim 1 is characterized in that: Draw a vector map of the suspected leaking area. The process is as follows: Randomly select a suspected leaking sub-region, extract all corresponding edge coordinates, and obtain the center point coordinates through the irregular shape region centroid algorithm; Combine any edge coordinates with the center point coordinates, and use the coordinate distance formula to get the suspected radius, and select the largest suspected radius as the circumscribed circle radius; Based on the center point coordinates and the circumscribed circle radius, all suspected leaking sub-areas are circumscribed to obtain a vector diagram of the suspected leaking area.

4. The pipeline network inspection management method based on SAR satellite detection data according to claim 1 is characterized in that: Combined with the underground pipeline GIS map, the process of obtaining the edge trend difference is as follows: Extract the coordinates of all feature points in the underground pipeline GIS map and connect them separately to obtain the feature edges to be superimposed; Extract the edge coordinates corresponding to all suspected water leakage sub-areas in the suspected water leakage area vector map, and connect them to obtain the reference feature edge; The feature edge to be superimposed is arbitrarily combined with the reference feature edge, and the starting point coordinates and the end point coordinates of the feature edge to be superimposed and the reference feature edge are extracted respectively. After being processed by the slope calculation formula, difference processing is performed and the absolute value is taken to obtain the edge trend difference.

5. The pipeline network inspection management method based on SAR satellite detection data according to claim 4 is characterized in that: Combined with the underground pipeline GIS map, the process of obtaining the edge degree difference is as follows: The coordinates of all points corresponding to the edge of the feature to be superimposed and the reference feature edge are extracted respectively, and the coordinates of the edge points of the feature to be superimposed are arbitrarily combined with the coordinates of the edge points of the reference feature to obtain multiple edge degree analysis groups, and the edge degree difference is obtained through the Euclidean distance formula.

6. The pipeline network inspection management method based on SAR satellite detection data according to claim 1 is characterized in that: The process of drawing a manual leak detection navigation map is as follows: The edge trend difference and edge degree difference are input into the geometric product method respectively, and the output is the superposition matching degree; If the overlay matching degree is less than or equal to the overlay matching standard degree, draw a manual leak detection navigation map; If the overlay matching degree is greater than the overlay matching standard degree, it is necessary to iteratively combine and analyze the feature edges 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 a manual leak detection navigation map.

7. The pipeline network inspection management method based on SAR satellite detection data according to claim 1 is characterized in that: Plan a simulated leak detection route and conduct a simulated leak detection test. The process is as follows: In the manual leak detection navigation map, multiple simulated leak detection routes are planned according to the Chinese Postman algorithm; Randomly select a simulated leak detection path, extract the suspected leak sub-area, and intercept the local simulated path that intersects with the simulated leak detection path; The coordinates of all points in the suspected leak sub-area and the local simulation path in the manual leak detection navigation map are extracted respectively, and the average processing is performed after processing by the Euclidean distance formula. The proportion of the total length of the simulated leak detection path is calculated to obtain the simulation distance evaluation value; The closed area formed by the local simulation path and the suspected leakage sub-area is marked as the simulation test area, and the ratio of the number of suspected leakage points to the total number of all suspected leakage points in the suspected leakage sub-area is counted and averaged to obtain the simulation proportion assessment value.

8. The pipeline network inspection management method based on SAR satellite detection data according to claim 7 is characterized in that: The effectiveness of artificial suspected water leak detection based on the simulated leak detection path is evaluated as follows: The ratio of the simulated proportion evaluation value to the simulated distance evaluation value is calculated 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.

9. The pipeline network inspection management method based on SAR satellite detection data according to claim 1 is characterized in that: Identify the local readjustment path within the leak detection path to be adjusted, replan and adjust it, and obtain an effective leak detection path. The process is as follows: Extract multiple local simulation paths in the leak detection path to be adjusted and process them to obtain a local evaluation value. If the local evaluation value is less than or equal to a local evaluation threshold, it is marked as a local readjustment path; Based on the starting point and end point of the local readjustment path, the least squares method is used for iterative fitting to obtain the corresponding local evaluation value, which is subtracted from the local evaluation threshold. The local readjustment path with the largest difference is selected and combined with other local simulation paths to draw an effective leak detection path.

10. The pipeline network inspection management system based on SAR satellite detection data is characterized by: include: Suspected water leakage identification module: Regularly observe the water supply network area through SAR satellite remote sensing images and identify suspected water leakage sub-areas; Overlay processing and drawing module: Draw a vector map of the suspected leaking area based on the suspected leaking sub-area and water supply network area, and overlay it 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 a simulated leak detection route, and conduct a simulated leak detection test to evaluate the effectiveness of manual suspected leak detection; Local identification and adjustment module: If the effectiveness is low, the local re-adjustment path within the leak detection path to be adjusted is identified to obtain an effective leak detection path.

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