A method for measuring the area of a leakage point for estimating the amount of water leakage in satellite leak detection

Abstract

The present invention relates to the technical field of satellite leak detection, and discloses a method for measuring the area of a leak point for estimating the amount of water leakage in satellite leak detection, which includes the following steps: measuring the area and mass of a rectangular cardboard; obtaining the shape and size of the leak hole of the water leakage point through plasticine; printing a part of the obtained shape and size of the leak hole with waterproof ink paste and transferring it to the cardboard; cutting out the part printed with the shape of the leak hole and measuring its mass; calculating the mass ratio of the cut-out part to the mass of the original rectangular cardboard to obtain the area of the leak hole of the water leakage point. The present invention breaks through the limitation of the leak hole form, is applicable to leak points of any complex shape, uses standard material ratio conversion to avoid the technical problem of directly measuring tiny holes, does not require special equipment, is simple to operate and low in cost, the measurement accuracy is guaranteed by the material uniformity, is applicable to different materials and environments, can be extended and applied to various leak detection scenarios, and has strong versatility.

Description

Technical Field

[0001] The present invention relates to the technical field of satellite leak detection, and particularly relates to a method for measuring the area of a leak point for estimating the water leakage volume in satellite leak detection. Background Art

[0002] Currently, methods for detecting water leakage in water supply pipe networks include pressure testing method, sound listening method, tracer method, DMA zoning management method, and satellite leak detection. After detecting a water leakage point through the above detection methods, it is necessary to further determine the water leakage volume of each leak point. Currently, there are 4 methods for measuring the water leakage volume, namely the volumetric method, the introduction method, the empirical method, and the empirical formula method.

[0003] Among them, the volumetric method and the introduction method cannot adapt to the water supply pressure not being the normal water supply pressure. For example, the inlet valve has been closed, the jet direction is upward, it is not easy to place a measuring cup in the jet direction, the water leakage along the pipe wall has a large flow rate, the position space of the leak point is too small to operate easily or the time spent on measuring the water leakage rate is long, it is impossible to tie a large-opening water collecting bag to the water leakage facility or blocking the free outflow of the orifice after tying.

[0004] In addition, the empirical method requires the visual inspection personnel to have rich practical experience in the area of the leak opening, the accuracy of estimating the water leakage volume is not high, and there is a lot of subjective components. The empirical formula method is a method recommended by the national standard "Standard for Leakage Control and Assessment of Urban Water Supply Pipe Networks" (CJJ92 - 2016). This method is suitable for all occasions, especially for occasions where it is difficult to implement the volumetric method and the introduction method. Among them, the empirical formula method requires obtaining the area of the leak orifice at the leak point and the pressure at the leak point. However, the "Standard for Leakage Control and Assessment of Urban Water Supply Pipe Networks" does not give a method for measuring the area of the leak orifice at the leak point, and the shapes of the leak orifices at the leak points are various, making it difficult to accurately measure the area of the leak orifice using ordinary measuring tools, resulting in the empirical formula method being difficult to use in reality.

[0005] The present invention proposes a method for measuring the area of a leak point for estimating the water leakage volume in satellite leak detection, which can simply, quickly, and accurately obtain the area of the leak orifice at the leak point. Summary of the Invention

[0006] The purpose of the present invention is to provide a method for measuring the area of a leak point for estimating the water leakage volume in satellite leak detection to solve at least one of the above-mentioned problems in the prior art.

[0007] In a first aspect, the present invention provides a method for measuring the area of a leak point for estimating the water leakage volume in satellite leak detection, including the following steps:

[0008] Measure the area and mass of a rectangular cardboard; obtain the shape and size of the leakage hole at the water leakage point through plasticine; print the shape and size part of the obtained leakage hole with waterproof ink paste and transfer it to the cardboard; cut out the part printed with the leakage hole shape and measure its mass; calculate the mass ratio of the cut-out part to the mass of the original rectangular cardboard to obtain the area of the leakage hole at the water leakage point;

[0009] After transferring the shape and area of the leakage hole at the water leakage point to the rectangular cardboard, perform sharpness analysis on the edge sub-regions of the transferred image, and extract the group of blurred edge sub-regions;

[0010] Based on the obtained group of blurred edge sub-regions, generate a set of cutting paths and select the optimal cutting path.

[0011] As a further solution of the present invention: The specific process of extracting the group of blurred edge sub-regions is as follows:

[0012] Calculate the variance of the gradient magnitude, compare it with the variance threshold. If the variance of the gradient magnitude ≤ the variance threshold, mark it as a blurred edge sub-region;

[0013] Integrate adjacent blurred edge sub-regions to obtain the group of blurred edge sub-regions.

[0014] As a further solution of the present invention: The process of obtaining the variance of the gradient magnitude is as follows:

[0015] Obtain the transferred image, and convert the color image into a grayscale image;

[0016] Extract the edge region of the transferred image, divide the edge region into several edge sub-regions, and for each edge sub-region;

[0017] Calculate the gradient components in the horizontal and vertical directions, and then calculate the gradient magnitude;

[0018] Obtain all pixel points within the edge sub-region and the corresponding gradient magnitude sequence, and calculate the variance of the gradient magnitude.

[0019] As a further solution of the present invention: The process of obtaining the set of cutting paths is as follows:

[0020] Determine its starting point and ending point through the contour tracking algorithm, and obtain the set of cutting paths based on the ant colony algorithm. The specific process is as follows:

[0021] Determine the positions and connection relationships of all blurred edge sub-regions, create a two-dimensional matrix to store the pheromone concentration between each node, and determine the number of ants participating in the path search;

[0022] Set the number of iterations of the algorithm and set the relevant parameters in the ant colony algorithm;

[0023] In each iteration, each ant independently conducts path search. When the preset number of iterations is reached, the algorithm terminates, and the set of paths obtained at this time is the set of cutting paths.

[0024] As a further solution of the present invention: The process of selecting the best cutting path includes:

[0025] For any cutting path, obtain all the inflection points on the cutting path;

[0026] Count the total number of inflection points and compare it with the inflection point number threshold. If the total number of inflection points < the inflection point number threshold, it is marked as a selectable cutting path.

[0027] As a further solution of the present invention: The process of selecting the best cutting path further includes:

[0028] Conduct data analysis on all selectable paths respectively, and calculate to obtain the inflection point difficulty coefficient, the average pheromone concentration, and the length coefficient;

[0029] Perform a product calculation on the average pheromone concentration and the length coefficient, and then perform a ratio calculation with the inflection point difficulty coefficient to obtain the cutting path selection index;

[0030] Extract the cutting path corresponding to the maximum value of the cutting path selection index as the best cutting path.

[0031] As a further solution of the present invention: The process of obtaining the inflection point difficulty coefficient is:

[0032] Calculate all the inflection point angles, and conduct data processing to calculate the ratio of high cutting difficulty angles and the high cutting difficulty degree value;

[0033] Calculate the distance between any two adjacent inflection points, arrange the distances in ascending order, and construct a distance sequence;

[0034] Calculate the Gini coefficient based on the distance sequence, which is the uniformity value;

[0035] Perform a weighted calculation on the ratio of high cutting difficulty angles, the high cutting difficulty degree value, and the uniformity value to obtain the inflection point difficulty coefficient.

[0036] As a further solution of the present invention: The process of obtaining the ratio of high cutting difficulty angles and the high cutting difficulty degree value is:

[0037] Mark the inflection point angles ≤ 90 degrees as low cutting difficulty angles, and mark the inflection point angles > 90 degrees as high cutting difficulty angles;

[0038] Count the number of high cutting difficulty angles and perform a ratio calculation with the total number of inflection points to obtain the ratio of high cutting difficulty angles;

[0039] Extract the inflection point angles corresponding to the high cutting difficulty angles, calculate the differences with the inflection point angle limits respectively, calculate the ratios of the differences to the inflection point angle limits, and then perform mean processing on the finally obtained ratios to obtain the high cutting difficulty degree value.

[0040] As a further solution of the present invention: the process of obtaining the average pheromone concentration is as follows:

[0041] Perform mean processing on the pheromone concentrations of all inflection points to obtain the average pheromone concentration.

[0042] As a further solution of the present invention: the process of obtaining the length coefficient is as follows:

[0043] Calculate the total length of the cutting path and perform normalization processing to obtain the length coefficient.

[0044] Advantages of the present invention:

[0045] 1. The present invention breaks through the limitation of the leak hole shape, is applicable to any complex-shaped leak points, adopts standard material ratio conversion, avoids the technical problem of directly measuring tiny holes, does not require special equipment, is easy to operate with low cost, the measurement accuracy is guaranteed by the material uniformity, is applicable to different materials and environments, can be extended and applied to various leak detection scenarios, and has strong versatility;

[0046] 2. The present invention can accurately determine the blurred area through the clarity analysis of the edge sub-regions of the transferred image, generates a set of cutting paths by using the ant colony algorithm, can explore more paths, increases the possibility of finding a suitable path, fully considers the cutting difficulty and path quality when selecting the best cutting path, can effectively reduce the measurement error caused by edge blurring, improve the accuracy of leak point area measurement, and further enhance the reliability of leak water volume estimation, thus enhancing the applicability and practicality of the entire measurement method. Description of the Drawings

[0047] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following will briefly introduce the drawings required for the description of the embodiments. Obviously, the following drawings are only some embodiments of the present invention. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0048] Figure 1 is a flowchart of a method for measuring the leak point area for estimating the leak water volume in satellite leak detection in Embodiment 1 of the present invention;

[0049] Figure 2 is a flowchart of a method for measuring the leak point area for estimating the leak water volume in satellite leak detection in Embodiment 2 of the present invention;

[0050] Figure 3 It is the architecture diagram of a leakage point area measurement system for satellite leak detection and water leakage estimation in the third embodiment of the present invention. Detailed implementation manners

[0051] In order to enable those skilled in the art to better understand the solution of the present invention, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0052] Embodiment 1

[0053] As Figure 1 shown, the embodiment of the present invention provides a method for measuring the area of a leakage point for satellite leak detection and water leakage estimation, which specifically includes the following steps:

[0054] Step 1: Prepare a cardboard with uniform texture and easy to absorb ink paste, and make an external matrix cardboard with both length and width slightly larger than the unfolded drawing of the leakage hole of the water supply pipe network leakage point for standby;

[0055] Obtain the cardboard area a1 by measuring the length and width, and at the same time use a precision electronic scale to weigh its mass as q1;

[0056] Step 2: Close the inlet valve of the water supply pipe network leakage point, cover the leakage hole of the leakage point with plasticine, and then gently press the plasticine so that the plasticine part is embedded into the leakage hole of the leakage point, obtain the convex shape and size of the plasticine of the leakage hole of the leakage point, and dry the water;

[0057] Step 3: Print the convex shape and size part of the leakage hole obtained by the plasticine with waterproof ink paste;

[0058] Step 4: Transfer the ink paste on the plasticine to the cardboard with uniform texture prepared in Step 1;

[0059] Step 5: Cut out the part with ink paste on the cardboard with the shape and size of the leakage hole of the leakage point, and weigh it with a precision electronic scale to obtain q2;

[0060] Step 6: Calculate the ratio of the mass of the cut-out part to the mass of the original rectangular cardboard to obtain the leakage point leakage hole area A;

[0061] Among them, the calculation formula for the leakage point leakage hole area A is: ;

[0062] It should be noted that the cardboard used in this example needs to have a uniform texture and a certain mass to improve the measurement accuracy. There are no requirements for the size and material, and any cardboard can be used. At the same time, the method described in this embodiment is also applicable to measuring the leakage water volume of the leakage points detected by non-satellite leak detection means;

[0063] Based on the above steps, the integrity of the measurement of the leakage hole area of the water supply network is given, and there are no requirements for the shape of the leakage points in the water supply network, which has strong applicability and application scope;

[0064] The technical solution of this embodiment is as follows: First, prepare a uniformly textured rectangular cardboard slightly larger than the unfolded diagram of the leakage hole, measure its initial area and mass, then cover the leakage hole with plasticine to obtain a three-dimensional shape, transfer the waterproof ink paste to the cardboard after drying, cut and weigh the ink paste area, and calculate the leakage hole area through mass ratio conversion. This method realizes area calculation by indirectly measuring the mass ratio of the ink paste covered area;

[0065] Thus, it can break through the limitation of the leakage hole shape, be applicable to any complex-shaped leakage points, use standard material ratio conversion to avoid the technical problem of directly measuring tiny holes, require no special equipment, be easy to operate with low cost, have the measurement accuracy guaranteed by the material uniformity, be applicable to different materials and environments, and can be extended and applied to various leak detection scenarios, with strong versatility.

[0066] Embodiment 2

[0067] Based on the above embodiment, as Figure 2 shown, obtaining the leakage point shape by transfer printing and measuring the leakage point area are key steps in calculating the leakage hole area of the leakage point. However, in actual operation, the transferred edge often appears blurred, which will lead to a large measurement error in the leakage point area and affect the accuracy of the leakage water volume estimation. A method for measuring the leakage point area for satellite leak detection water volume estimation provided by an embodiment of the present invention specifically includes the following steps:

[0068] After transferring the ink paste on the plasticine to a pre-prepared uniformly textured cardboard, perform clarity analysis on the edge sub-regions of the transferred image and extract the group of blurred edge sub-regions;

[0069] In some embodiments, obtain the transferred image and perform digital processing on the transferred image using image processing software. Among them, the image processing software includes but is not limited to: Adobe Photoshop, open-source ImageJ software;

[0070] After importing the image, convert the color image to a grayscale image;

[0071] Exemplarily, when processing using Adobe Photoshop, "Grayscale" can be selected through "Mode" under the "Image" menu. Grayscale images simplify image information into a single grayscale value, facilitating subsequent edge detection and clarity analysis;

[0072] Extract the edge region of the transferred image, that is, the border region;

[0073] Divide the edge region into several edge sub-regions. For each edge sub-region;

[0074] It should be noted that in order to increase the accuracy of clarity analysis of edge sub-regions, when dividing the edge region into sub-regions, the edge region needs to be subdivided into as small sub-regions as possible;

[0075] Use the Sobel operator or Prewitt operator to calculate its gradient components in the horizontal and vertical directions and , according to the formula: , calculate the gradient magnitude G;

[0076] Obtain n pixel points within the edge sub-region, and obtain the gradient magnitude sequence corresponding to the n pixel points, that is , then the mean value of the gradient magnitude : , where represents the i-th gradient magnitude;

[0077] According to the formula: , calculate the variance of the gradient magnitude;

[0078] Set a variance threshold, and compare the variance of the gradient magnitude with the variance threshold;

[0079] If the variance of the gradient magnitude is greater than the variance threshold, mark the corresponding edge sub-region as a clear edge sub-region;

[0080] If the variance of the gradient magnitude is less than or equal to the variance threshold, mark the corresponding edge sub-region as a blurred edge sub-region;

[0081] Extract all the blurred edge sub-regions, and integrate adjacent blurred edge sub-regions to obtain a group of blurred edge sub-regions;

[0082] Thus, by extracting the image edge region and dividing it into sub-regions, and using the Sobel or Prewitt operator to calculate the gradient magnitude, the position and orientation of the image edge can be accurately determined, which is crucial for obtaining the accurate shape of the leakage point, providing a basis for subsequent leakage point area measurement, and improving the measurement accuracy;

[0083] By calculating the mean and variance of the gradient magnitudes of each edge sub-region and comparing them with a set threshold, the clarity of the edge sub-region can be accurately judged, and the clear and blurred regions can be marked, which helps to process the blurred regions specifically, reduce the measurement error caused by edge blurring, and improve the reliability of the entire measurement result;

[0084] Based on the obtained set of blurred edge sub-regions, generate a set of cutting paths and select the optimal cutting path;

[0085] In some embodiments, obtain all sets of blurred edge sub-regions and based on any one set of blurred edge sub-regions;

[0086] Taking the two ends of the set of blurred edge sub-regions as the starting point and the ending point respectively, generate a set of cutting paths. The specific process is as follows:

[0087] Determine its starting point and ending point through a contour tracking algorithm, and obtain a set of cutting paths based on simulating the foraging behavior of ants (ant colony algorithm);

[0088] Determine the positions and connection relationships of all blurred edge sub-regions, which can be represented in the form of a graph. Each sub-region is a node in the graph, and the connection between nodes indicates that it is possible to reach one sub-region from another sub-region;

[0089] Create a two-dimensional matrix to store the pheromone concentration between each pair of nodes. Initially, the pheromone concentration between all pairs of nodes can be set to the same constant, such as 1;

[0090] Determine the number of ants participating in the path search. Among them, the more ants there are, the wider the range of explored paths, but the computational amount will also increase accordingly;

[0091] Set the number of iterations of the algorithm, that is, the number of times the ants make multiple foraging attempts;

[0092] Set the relevant parameters in the ant colony algorithm;

[0093] Exemplarily, the relevant parameters are: pheromone evaporation coefficient ρ (the value range is 0.1 - 0.9), heuristic factor α (controlling the importance of pheromone), and expected heuristic factor β (controlling the importance of distance heuristic information);

[0094] In each iteration, each ant independently conducts path search. The specific process is as follows:

[0095] Each ant randomly selects a sub-region as the starting node;

[0096] When an ant is at a certain node, the transition probability is calculated based on the pheromone concentration and heuristic information (such as the reciprocal of the distance) between this node and other unvisited nodes, and then the next node is randomly selected according to this probability. The transition probability formula is as follows:

[0097] ;

[0098] Among them, represents the probability that the k-th ant transfers from node p to node j. k represents the ant number, used to distinguish different ant individuals. p represents the node number where the ant is currently located, and j represents the target node number that the ant may transfer to. represents the pheromone concentration between node i and node j. α represents the pheromone importance factor, used to control the weight of the pheromone concentration in the calculation of the transition probability. represents the heuristic information. β represents the expected heuristic factor, used to control the weight of the heuristic information in the calculation of the transition probability. represents the set of nodes that the k-th ant has not visited yet. s is an index variable used for summation operations;

[0099] Whenever an ant selects a new node, it adds it to the current path and marks the node as visited;

[0100] When the ant has visited all sub-regions, a complete path is formed;

[0101] After each ant completes the path search, the pheromone on the path needs to be updated. The pheromone update is local, and the local update formula is as follows:

[0102]

[0103] Among them, ρ represents the pheromone evaporation coefficient, represents the pheromone increment of this update, which can be determined according to the situation of the ant passing through this path;

[0104] In each iteration, the paths generated by each ant are recorded to form a path set. As the number of iterations increases, the path set will continue to enrich and contain more different paths;

[0105] When the preset number of iterations is reached, the algorithm terminates. At this time, the obtained path set is the trimmed path set;

[0106] Based on the obtained trimmed path set, the best trimmed path is selected. The specific process is as follows:

[0107] For any trimmed path, all inflection points on the trimmed path are obtained;

[0108] It should be noted that the inflection point refers to the point where the path direction changes significantly in the clipping path. When the ant searches for the path, it will select the next node according to the pheromone concentration and heuristic information. When the choice made by the ant at a certain node causes a large change in the path direction, this node becomes an inflection point;

[0109] Count the total number of inflection points and compare the total number of inflection points with the inflection point quantity threshold. Among them, the inflection point total quantity threshold is set by those skilled in the art based on the clipping experience and the maximum number of inflection points within the path length. The inflection point quantity thresholds corresponding to clipping paths of different lengths are different;

[0110] Exemplarily, when the length of the clipping path is 10 cm, when the number of inflection points exceeds 8, the clipping operation difficulty increases significantly. Then the inflection point quantity threshold can be set to 7;

[0111] If the total number of inflection points is greater than or equal to the inflection point quantity threshold, it indicates that the clipping difficulty of this clipping path is relatively large, and this clipping path is marked as an unselectable clipping path;

[0112] It should be noted that if all the clipping paths are unselectable clipping paths, then select the clipping path corresponding to the minimum value of the total number of inflection points as the optimal clipping path;

[0113] If the total number of inflection points is less than the inflection point quantity threshold, it indicates that the clipping difficulty of this clipping path is within the operable range, and this clipping path is marked as a selectable clipping path;

[0114] Based on all the selectable paths, calculate all the inflection point angles (i.e., the turning angles of the path at the inflection points);

[0115] Taking 90 degrees as the inflection point angle limit value, mark the inflection point angles less than or equal to 90 degrees as low clipping difficulty angles, and mark the inflection point angles greater than 90 degrees as high clipping difficulty angles;

[0116] Count the number of high clipping difficulty angles and calculate the ratio with the total number of inflection points to obtain the ratio of high clipping difficulty angles;

[0117] Extract the inflection point angles corresponding to the high clipping difficulty angles, calculate the differences with the inflection point angle limit value respectively, calculate the ratio of the differences to the inflection point angle limit value, and finally perform an average process on the obtained ratios to obtain the high clipping difficulty degree value;

[0118] Based on any two adjacent inflection points, calculate the distance between the two inflection points. Specifically, use the Euclidean distance formula to calculate the distance between adjacent inflection points;

[0119] Arrange all the calculated distances in ascending order and construct a distance sequence: , where h is the total number of inflection points;

[0120] Use the Gini coefficient to characterize the uniformity value of the inflection point distribution. The specific process is as follows:

[0121] The calculation formula for the cumulative distance ratio is: , where represents the cumulative distance ratio, t = 1, 2,..., h - 1; represents the sum of the first i distances after sorting, represents the sum of all h - 1 distances;

[0122] According to the formula , calculate the inflection point ratio , where t represents which distance is currently being calculated (corresponding to the (i + 1)-th inflection point), and n - 1 is the total number of distances (n is the number of inflection points);

[0123] Calculate the Gini coefficient M. The formula is:

[0124] ;

[0125] where represents the summation operation from t = 1 to t = h - 2;

[0126] It should be noted that the value range of the Gini coefficient is between [0, 1]. The closer the M value is to 0, the more uniform the inflection point distribution on the cutting path. The closer the M value is to 1, the more uneven the inflection point distribution on the cutting path;

[0127] Calculating the Gini coefficient M is the uniformity value;

[0128] Perform a weighted summation calculation on the high-angle ratio of the cutting difficulty, the high-degree value of the cutting difficulty, and the uniformity value to obtain the inflection point difficulty coefficient;

[0129] Among them, the larger the inflection point difficulty coefficient, the greater the cutting difficulty of the corresponding cutting path, and the lower the priority of selecting it as the best cutting path;

[0130] Obtain the pheromone concentration of all inflection points and perform an average treatment to obtain the average pheromone concentration;

[0131] Among them, the pheromone concentration at the inflection point can reflect the preference degree of ants to choose this path. A high pheromone concentration indicates that more ants choose to pass through this inflection point, which means that this path is better, and the priority of selecting it as the best cutting path is higher;

[0132] Calculate the total length of the cutting path and perform a normalization process to obtain the length coefficient;

[0133] Exemplarily, divide the shortest path length by the current path length to obtain the evaluation index value of the path length. The closer this value is to 1, that is, the larger the length coefficient, the better the path length, and the higher the priority of selecting it as the best cutting path;

[0134] Calculate the product of the average pheromone concentration and the length coefficient, and then calculate the ratio with the inflection point difficulty coefficient to obtain the cutting path selection index;

[0135] Obtain the cutting path selection indexes corresponding to all cutting paths, and extract the cutting path corresponding to the maximum value of the cutting path selection index as the best cutting path;

[0136] The effect of using inflection points for in-depth analysis is as follows: In determining the feasibility of the cutting path, by counting the total number of inflection points and comparing it with the threshold, the cutting difficulty of the cutting path can be intuitively judged. If the total number is greater than or equal to the threshold, it can be marked as an unselectable path to prevent selecting a path with too high cutting difficulty and ensure the operability of the operation;

[0137] In evaluating the difficulty of the cutting path, analyze the inflection point angles, distinguish the low-angle and high-angle cutting difficulties with 90 degrees as the limit value, and obtain the high-degree cutting difficulty value by counting the ratio of the number of high angles to the total number and calculating the average value of the difference between the high angles and the limit value, which can more carefully measure the cutting difficulty of the path in terms of angle change;

[0138] In considering the quality of the cutting path, calculate the Gini coefficient to characterize the uniformity of the inflection point distribution. The closer the Gini coefficient is to 0, the more uniform the inflection point distribution, and the higher the path quality, providing a quantitative index for judging the quality of the path;

[0139] Combining these analysis results based on inflection points and combining the average pheromone concentration and the length coefficient can comprehensively and deeply evaluate the cutting path. Finally, by calculating the cutting path selection index, the most suitable best cutting path is selected, greatly improving the scientificity and accuracy of path selection in the process of measuring the leakage point area, reducing the measurement error caused by unreasonable paths, and effectively enhancing the reliability and practicality of the entire water leakage estimation method;

[0140] The technical solution of this embodiment is as follows: First, perform grayscale processing on the transferred image, calculate the average value and variance of the gradient amplitude of the edge sub-region, screen out the blurred edge region through the variance threshold, then generate a set of cutting paths based on the ant colony algorithm, construct a selection model by integrating multi-dimensional indexes such as the uniformity of inflection point distribution, path length, and pheromone concentration, and finally determine the optimal cutting path;

[0141] By analyzing the clarity of the edge sub-regions of the transferred image, the blurred region can be accurately determined, providing a basis for subsequent processing. Using the ant colony algorithm to generate a set of cutting paths can explore more paths and increase the possibility of finding a suitable path. When selecting the best cutting path, multiple factors are comprehensively evaluated, fully considering the cutting difficulty and path quality, which can effectively reduce the measurement error caused by edge blurring, improve the accuracy of leak point area measurement, and further enhance the reliability of estimated water leakage volume, thereby enhancing the applicability and practicality of the entire measurement method.

[0142] Embodiment 3

[0143] Based on the above embodiments, as Figure 3 shown, a leak point area measurement system for estimating water leakage volume in satellite leak detection provided by an embodiment of the present invention specifically includes:

[0144] Clarity analysis module: After transferring the ink paste on the plasticine to a pre-prepared cardboard with uniform texture, analyze the clarity of the edge sub-regions of the transferred image and extract the group of blurred edge sub-regions;

[0145] Cutting path selection module: Based on the obtained group of blurred edge sub-regions, generate a set of cutting paths and select the best cutting path.

[0146] In the above embodiments, the descriptions of each embodiment have their own focuses. For parts not detailed or recorded in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0147] The above formulas are all dimensionless and take their numerical values for calculation. The formulas are obtained by collecting a large amount of data for software simulation to obtain a formula closest to the actual situation. The preset parameters in the formulas are set by those skilled in the art according to the actual situation.

[0148] The above has described a detailed description of an embodiment of the present invention, but the content described is only a preferred embodiment of the present invention and cannot be considered as limiting the scope of implementation of the present invention. All equivalent changes and improvements made according to the scope of the present invention application should still fall within the scope covered by the patent of the present invention.

Claims

1. A method for measuring the leakage point area for satellite leakage detection and water leakage estimation, characterized in that: The following steps are involved: Measure the area and mass of the rectangular cardboard; obtain the shape and size of the leaking hole through plasticine; print the obtained shape and size of the leaking hole with waterproof ink and transfer it to the cardboard; cut out the part printed with the shape of the leaking hole and measure its mass; Calculate the ratio of the mass of the cut-out part to the mass of the original rectangular cardboard to obtain the area of ​​the leaking hole; After the shape and area of ​​the leaking hole are transferred onto a rectangular paperboard, the edge sub-region of the transferred image is analyzed for clarity to extract the fuzzy edge sub-region group; Based on the obtained fuzzy edge sub-region group, a clipping path set is generated and an optimal clipping path is selected; For any clipping path, get all the inflection points on the clipping path; Count the total number of inflection points and compare it with the inflection point number threshold. If the total number of inflection points is less than the inflection point number threshold, it is marked as an optional clipping path. Calculate all inflection point angles and perform data processing to obtain the percentage of angles with high cutting difficulty and the degree of cutting difficulty; Calculate the distance between any two adjacent inflection points, arrange the distances in ascending order, and construct a distance sequence; The Gini coefficient calculated based on the distance sequence is the uniformity value; Mark the inflection point angles ≤ 90 degrees as angles with low trimming difficulty, and mark the inflection point angles > 90 degrees as angles with high trimming difficulty; Count the number of angles with high cutting difficulty and calculate the ratio with the total number of inflection points to obtain the ratio of angles with high cutting difficulty; Extract the inflection point angle corresponding to the angle with high cutting difficulty, and perform difference calculation with the inflection point angle limit respectively, perform ratio calculation on the difference and the inflection point angle limit, and then perform average processing on the finally obtained ratio to obtain the high degree of cutting difficulty; The inflection point difficulty coefficient is obtained by weighting the proportion of high-difficulty cutting angles, the high-difficulty cutting degree and the uniformity value. Calculate the total length of the clipping path and perform normalization to obtain the length coefficient; The mean pheromone concentration was calculated; The mean pheromone concentration and the length coefficient are multiplied and then the ratio is calculated with the inflection point difficulty coefficient to obtain the trimming path selection index; The clipping path corresponding to the maximum value of the clipping path selection index is extracted as the optimal clipping path.

2. The method for measuring the leakage point area for satellite leak detection and water leakage estimation according to claim 1, characterized in that: The specific process of extracting the fuzzy edge sub-region group is as follows: Calculate the gradient amplitude variance and compare it with the variance threshold. If the gradient amplitude variance is less than or equal to the variance threshold, mark it as a fuzzy edge sub-region. Adjacent fuzzy edge sub-regions are integrated to obtain a fuzzy edge sub-region group.

3. The method for measuring the leakage point area for satellite leak detection and water leakage estimation according to claim 2, characterized in that: The process of obtaining the gradient amplitude variance is: Acquire the transferred image and convert the color image into a grayscale image; Extracting the edge region of the transferred image, dividing the edge region into a plurality of edge sub-regions, for each edge sub-region; Calculate the gradient components in the horizontal and vertical directions, and then calculate the gradient amplitude; Get all pixel points in the edge sub-region and the corresponding gradient amplitude sequence, and calculate the gradient amplitude variance.

4. The method for measuring the leakage point area for satellite leakage detection and water leakage estimation according to claim 1, characterized in that: The process of obtaining the clipping path set is as follows: The starting point and the end point are determined by the contour tracking algorithm, and the clipping path set is obtained based on the ant colony algorithm. The specific process is as follows: Determine the location and connection relationship of all fuzzy edge sub-areas, create a two-dimensional matrix to store the pheromone concentration between each node, and determine the number of ants participating in the path search; Set the number of iterations of the algorithm and set the relevant parameters in the ant colony algorithm; In each iteration, each ant searches for a path independently. When the preset number of iterations is reached, the algorithm terminates and the path set obtained at this time is the clipping path set.

5. The method for measuring the leakage point area for satellite leakage detection and water leakage estimation according to claim 1, characterized in that: The process of obtaining the mean pheromone concentration is as follows: The pheromone concentrations of all inflection points are averaged to obtain the mean pheromone concentration.

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