Leakage point area measurement method for satellite leakage detection water leakage amount estimation

Abstract

The invention relates to the technical field of satellite leakage detection, and discloses a leakage point area measurement method for satellite leakage detection water leakage amount estimation, which comprises the following steps of: measuring the area and the mass of a rectangular paperboard; the shape and the size of the leakage hole of the water leakage point are obtained through plasticine; printing waterproof inkpad on the obtained shape and size part of the leak hole, and transferring the leak hole to a paperboard; the part printed with the leak hole shape is cut out, and the quality of the part is measured; and calculating the mass ratio of the cut part to the original rectangular paperboard to obtain the area of the leakage hole of the water leakage point. The method breaks through the limitation of the leakage hole form, is suitable for any leakage point in a complex shape, adopts standard material proportion conversion, avoids the technical problem of direct measurement of micro holes, does not need special equipment, is simple and convenient to operate, is low in cost, is suitable for different materials and environments, can be expanded and applied to various leakage detection scenes, and is high in universality; the measurement precision is guaranteed by material uniformity.

Description

Technical Field

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

[0002] At present, the methods for detecting water supply network leakage include pressure test method, listening method, tracer method, DMA zoning management method and satellite leak detection. After detecting the leakage point through the above detection methods, it is necessary to further determine the leakage amount of each leakage point. At present, there are 4 methods to measure the leakage amount, namely volume method, introduction method, empirical method and empirical formula method; Among them, the volumetric method and the introduction method cannot adapt to the water supply pressure that is not the normal water supply pressure, for example, the water inlet valve has been closed, the jet direction is upward, it is difficult to place a measuring cup in the jet direction, the leakage flow along the pipe wall is large, the space at the leakage point is too small to be operated, or it takes a long time to measure the leakage rate, it is impossible to tie the large-opening water bag to the leaking facility or the free outflow of the orifice is blocked after tying, etc. In addition, the empirical method requires the visual inspector to have rich practical experience in leak area, the estimation accuracy of leakage is not high, and there are many subjective elements. The empirical formula method is the method recommended by the national standard "Standard for Control and Assessment of Leakage in Urban Water Supply Pipe Networks" (CJJ92-2016). This method is suitable for all occasions, especially for occasions where the volumetric method and the introduction method are difficult to implement. The empirical formula method requires the leakage point leakage area and the pressure of the leakage point, but the "Standard for Control and Assessment of Leakage in Urban Water Supply Pipe Networks" does not provide a method for measuring the leakage point leakage area. The leakage point leakage area has different shapes, and it is difficult to accurately measure the leakage area using ordinary measuring tools, which makes the empirical formula method difficult to use in reality. The invention proposes a leakage point area measurement method for satellite leakage detection and water leakage estimation, which can simply, quickly and accurately obtain the leakage point leakage hole area. Summary of the invention

[0003] The object of the present invention is to provide a leakage point area measurement method for satellite leakage detection and water leakage estimation, so as to solve at least one of the above-mentioned prior art problems.

[0004] In a first aspect, the present invention provides a method for measuring the leakage point area for satellite leakage detection and water leakage estimation, comprising the following steps: 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 on 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.

[0005] As a further solution of the present invention: the specific process of extracting the fuzzy edge sub-region group is: 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.

[0006] As a further solution of the present invention: 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.

[0007] As a further solution of the present invention: the process of obtaining the clipping path set is: 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.

[0008] As a further solution of the present invention: the process of selecting the best clipping path includes: For any clipping path, get all the inflection points on the clipping path; The total number of inflection points is counted and compared 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.

[0009] As a further solution of the present invention: the process of selecting the best clipping path also includes: Data analysis was performed on all the optional paths to calculate the inflection point difficulty coefficient, pheromone concentration mean and length coefficient; 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.

[0010] As a further solution of the present invention: the process of obtaining the inflection point difficulty coefficient is: 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; The inflection point difficulty coefficient is obtained by weighted calculation of the proportion of high cutting difficulty angles, high cutting difficulty degree and uniformity value.

[0011] As a further solution of the present invention: the process of obtaining the high-difficulty cutting angle ratio value and the high-difficulty cutting degree value is as follows: 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; The inflection point angle corresponding to the angle with high cutting difficulty is extracted, and the difference between the angle and the inflection point angle limit is calculated respectively, and the ratio of the difference and the inflection point angle limit is calculated. Then, the final ratio is averaged to obtain the high degree of cutting difficulty value.

[0012] As a further solution of the present invention: the process of obtaining the mean pheromone concentration is: The pheromone concentrations of all inflection points are averaged to obtain the mean pheromone concentration.

[0013] As a further solution of the present invention: the process of obtaining the length coefficient is: The total length of the clipping path is calculated and normalized to obtain the length coefficient.

[0014] Beneficial effects of the present invention: 1. The present invention breaks through the limitation of leak hole shape and is applicable to leak points of any complex shape. It adopts standard material ratio conversion to avoid the technical difficulties of directly measuring tiny holes. It does not require special equipment, is easy to operate and has low cost. The measurement accuracy is guaranteed by the uniformity of the material. It is applicable to different materials and environments, and can be expanded to various leak detection scenarios with strong versatility. 2. The present invention can accurately determine the fuzzy area by analyzing the clarity of the edge sub-area of ​​the transferred image, and generate a clipping path set using the ant colony algorithm, which can explore more paths and increase the possibility of finding a suitable path. When selecting the optimal clipping path, the clipping difficulty and path quality are fully considered, which can effectively reduce the measurement error caused by edge blur, improve the accuracy of leakage area measurement, and thus improve the reliability of leakage estimation, thereby enhancing the applicability and practicality of the entire measurement method. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0016] Figure 1 It is a flow chart of a leakage point area measurement method for satellite leakage detection and water leakage estimation in embodiment 1 of the present invention; Figure 2 It is a flow chart of a leakage point area measurement method for satellite leakage detection and water leakage estimation in Embodiment 2 of the present invention; Figure 3 It is an architecture diagram of a leakage point area measurement system for satellite leak detection and water leakage estimation in embodiment 3 of the present invention. DETAILED DESCRIPTION

[0017] In order to enable those skilled in the art to better understand the scheme of the present invention, the technical scheme in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the present invention.

[0018] Embodiment 1 like Figure 1 As shown, an embodiment of the present invention provides a leakage point area measurement method for satellite leakage detection and water leakage estimation, which specifically includes the following steps: Step 1: Prepare a cardboard with uniform texture and easy to absorb ink, and make an external matrix cardboard with a length and width slightly larger than the expansion diagram of the water supply network leakage point and leakage hole for use; The area of ​​the cardboard is a1, which is obtained by measuring the length and width, and its mass is q1, which is weighed by a precision electronic scale. Step 2: Close the water inlet valve at the leaking point of the water supply network, cover the leaking hole with plasticine, and then gently press the plasticine to make the plasticine part embedded in the leaking hole, obtain the convex shape and size of the plasticine at the leaking hole, and dry the water; Step 3: Print the raised shape and size of the leak obtained by the plasticine with waterproof ink; Step 4: Transfer the ink on the plasticine to the cardboard with uniform texture prepared in step 1; Step 5: Cut out the part with ink on the cardboard with the shape and size of the leaking hole, and weigh it with a precision electronic scale to obtain q2; Step 6: Calculate the ratio of the cut-out mass to the mass of the original rectangular cardboard to obtain the leakage area A; Among them, the calculation formula for the leakage point leakage area A is: ; It should be noted that the cardboard used in this example needs to have a uniform texture and a certain quality to improve the measurement accuracy. There is no requirement for size and material, and all can be used. At the same time, the method described in this embodiment is also applicable to measuring the leakage amount of the leak point detected by non-satellite leak detection means; Based on the above steps, the integrity of the measurement of the leakage area of ​​the water supply network is given, and there is no requirement for the shape of the leakage point of the water supply network, which has strong applicability and application range; The technical solution of this embodiment is as follows: first, a uniform rectangular cardboard with a texture slightly larger than the expanded image of the leak hole is prepared, and its initial area and mass are measured. Then, the leak hole is covered with plasticine to obtain a three-dimensional shape. After drying, waterproof ink is transferred to the cardboard, and the ink area is cut and weighed. The area of ​​the leak hole is converted by the mass ratio. This method realizes area calculation by indirectly measuring the mass ratio of the ink-covered area. This can break through the limitations of leak hole shape and is suitable for leaks of any complex shape. It uses standard material ratio conversion to avoid the technical difficulties of directly measuring tiny holes. It does not require special equipment and is easy to operate and low cost. The measurement accuracy is guaranteed by the uniformity of the material. It is suitable for different materials and environments and can be expanded to a variety of leak detection scenarios with strong versatility.

[0019] Embodiment 2 Based on the above embodiments, Figure 2 As shown, obtaining the shape of the leakage point by transfer and measuring the leakage point area are key steps in calculating the leakage point and leakage hole area. However, in actual operation, the transfer edge often has a fuzzy problem, which will lead to a large error in the measurement of the leakage point area and affect the accuracy of the leakage amount estimation. The embodiment of the present invention provides a leakage point area measurement method for satellite leakage detection leakage amount estimation, which specifically includes the following steps: After the ink pad on the plasticine is transferred to the pre-prepared cardboard with uniform texture, the edge sub-region of the transferred image is analyzed for clarity to extract the fuzzy edge sub-region group; In some embodiments, the transferred image is obtained, and the transferred image is digitally processed using image processing software, wherein the image processing software includes but is not limited to: Adobe Photoshop, open source ImageJ software; After importing the image, convert the color image to grayscale; For example, when using Adobe Photoshop for processing, you can select "Grayscale" through "Mode" under the "Image" menu. The grayscale image simplifies the image information into a single grayscale value, which is convenient for subsequent edge detection and clarity analysis; Extracting the edge area of ​​the transferred image, i.e., the frame area; Divide the edge region into a number of edge sub-regions, and for each edge sub-region; It should be noted that in order to increase the accuracy of the edge sub-region clarity analysis, when dividing the edge region into sub-regions, the edge region needs to be subdivided into sub-regions as small as possible; 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 amplitude G; Get n pixels in the edge sub-region and get the gradient amplitude sequence corresponding to the n pixels, that is, , then the mean value of the gradient amplitude is : ,in, represents the i-th gradient amplitude; According to the formula: , calculate the variance of the gradient amplitude; Set the variance threshold and compare the variance of the gradient amplitude with the variance threshold; If the variance of the gradient amplitude is greater than the variance threshold, the corresponding edge sub-region is marked as a clear edge sub-region; If the variance of the gradient amplitude is less than or equal to the variance threshold, the corresponding edge sub-region is marked as a fuzzy edge sub-region; Extract all fuzzy edge sub-regions, integrate adjacent fuzzy edge sub-regions to obtain a fuzzy edge sub-region group; Therefore, by extracting the edge area of ​​the image and dividing it into sub-areas, and using the Sobel or Prewitt operator to calculate the gradient amplitude, the position and direction of the image edge can be accurately determined, which is crucial to obtaining the accurate shape of the leak point, providing a basis for subsequent leak point area measurement and improving the accuracy of the measurement; By calculating the mean and variance of the gradient amplitude of each edge sub-region and comparing it with the set threshold, the clarity of the edge sub-region can be accurately judged, and the clear and blurred areas can be marked, which helps to deal with the blurred areas in a targeted manner, reduce the measurement errors caused by edge blur, and improve the reliability of the entire measurement results; Based on the obtained fuzzy edge sub-region group, a clipping path set is generated and an optimal clipping path is selected; In some embodiments, all fuzzy edge sub-region groups are obtained based on any fuzzy edge sub-region group; The two ends of the fuzzy edge sub-region group are the starting point and the end point respectively, and a clipping path set is generated. The specific process is as follows: The starting and ending points are determined by the contour tracking algorithm, and the clipping path set is obtained based on the simulation of ant foraging behavior (ant colony algorithm); Determine the location and connection relationship of all fuzzy 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 one sub-region can be reached from another sub-region. Create a two-dimensional matrix to store the pheromone concentration between each node. Initially, the pheromone concentration between all node pairs can be set to the same constant, such as 1; Determine the number of ants participating in the path search. The more ants there are, the wider the path explored, but the amount of calculation will also increase accordingly. Set the number of iterations of the algorithm, that is, the number of foraging attempts made by the ants; Set relevant parameters in the ant colony algorithm; Exemplarily, the relevant parameters are: pheromone volatility coefficient ρ (value range 0.1-0.9), heuristic factor α (controls the importance of pheromone) and expectation heuristic factor β (controls the importance of distance heuristic information); In each iteration, each ant searches for a path independently, and the specific process is as follows: Each ant randomly selects a subregion as the starting node; When an ant is at a node, the transition probability is calculated based on the pheromone concentration and heuristic information (such as the inverse of the distance) between the node and other unvisited nodes, and then the next node is randomly selected according to this probability. The transition probability formula is as follows: ; in, represents the probability of the kth ant transferring from node p to node j, k represents the ant number, which is 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. It refers to the pheromone concentration between node i and node j, α represents the pheromone importance factor, which is used to control the weight of pheromone concentration in the calculation of transition probability. represents the heuristic information, β represents the expected heuristic factor, which is used to control the weight of the heuristic information in the calculation of the transition probability. represents the set of nodes that the kth ant has not visited yet, and s is an index variable used for summation operation; Every time an ant selects a new node, it adds it to the current path and marks the node as visited; When the ant has visited all sub-areas, a complete path is formed; After each ant completes the path search, the pheromone on the path needs to be updated. The pheromone update is a local update. The local update formula is as follows: Where ρ represents the pheromone volatility coefficient, Indicates the pheromone increment of this update, which can be determined based on the situation of ants passing through the path; In each iteration, the path generated by each ant is recorded to form a path set. As the number of iterations increases, the path set will continue to be enriched to include more different paths. When the preset number of iterations is reached, the algorithm terminates, and the path set obtained at this time is the clipping path set; Based on the obtained clipping path set, the best clipping path is selected. The specific process is as follows: For any clipping path, get all the inflection points on the clipping path; It should be explained that the inflection point refers to the point where the path direction changes significantly in the clipping path. When searching for a path, the ant will choose the next node based on the pheromone concentration and heuristic information. When the choice made by the ant at a certain node causes a significant change in the path direction, this node becomes an inflection point. Count the total number of inflection points, and compare the total number of inflection points with the inflection point number threshold, wherein the inflection point total number threshold is summarized and set by those skilled in the art based on trimming experience and the maximum number of inflection points within the path length, and trimming paths of different lengths correspond to different inflection point number thresholds; For example, if the length of the clipping path is 10 centimeters, when the number of inflection points exceeds 8, the difficulty of the clipping operation increases significantly, and the threshold value of the number of inflection points can be set to 7; If the total number of inflection points is greater than or equal to the inflection point number threshold, it means that the clipping path is difficult to clip, and the clipping path is marked as an unselectable clipping path; It should be noted that if all clipping paths are non-selectable clipping paths, the clipping path corresponding to the minimum total number of inflection points is selected as the optimal clipping path; If the total number of inflection points is less than the inflection point number threshold, it means that the clipping difficulty of the clipping path is within the operable range, and the clipping path is marked as an optional clipping path; Based on all the selectable paths, calculate all the turning point angles (i.e. the turning angles of the paths at the turning points); With 90 degrees as the inflection point angle limit, inflection point angles less than or equal to 90 degrees are marked as angles with low cutting difficulty, and inflection point angles greater than 90 degrees are marked as angles with high cutting 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, perform average processing on the finally obtained ratio, and obtain the high degree of cutting difficulty; Based on any two adjacent inflection points, the distance between the two inflection points is calculated, and specifically the distance between adjacent inflection points is calculated using the Euclidean distance formula; Arrange all the calculated distances in ascending order and construct a distance sequence: , where h is the total number of inflection points; The Gini coefficient is used to characterize the uniformity of the inflection point distribution. The specific process is as follows: The calculation formula for the cumulative distance ratio is: ,in, 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; According to the formula , calculate the inflection point ratio , where t represents the distance currently being calculated (corresponding to the i+1th inflection point), and n-1 is the total number of distances (n is the number of inflection points); The formula for calculating the Gini coefficient M is: ; in, It means to perform sum operation from t=1 to t=h-2; 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 evenly the inflection points on the clipping path are distributed. The closer the M value is to 1, the more unevenly the inflection points on the clipping path are distributed. The calculated Gini coefficient M is the uniformity value; The weighted sum of the high-difficulty-cutting angle ratio, the high-difficulty-cutting degree and the uniformity value is calculated to obtain the inflection point difficulty coefficient; Among them, the greater the inflection point difficulty coefficient is, the greater the clipping difficulty of the corresponding clipping path is, and the lower the priority of selecting it as the optimal clipping path is; Obtain the pheromone concentrations of all inflection points and perform mean processing to obtain the mean pheromone concentration; Among them, the pheromone concentration at the inflection point can reflect the preference of ants for choosing this path. The higher the pheromone concentration, the more ants choose to pass through this inflection point, which means that this path is better and the higher the priority of choosing it as the best clipping path; Calculate the total length of the clipping path and perform normalization to obtain the length coefficient; Exemplarily, the shortest path length is divided by the current path length to obtain the evaluation index value of the path length. The closer the value is to 1, that is, the larger the length coefficient is, the better the path length is, and the higher the priority of selecting it as the optimal clipping path; 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; Obtain the clipping path selection indexes corresponding to all clipping paths, and extract the clipping path corresponding to the maximum value of the clipping path selection index as the optimal clipping path; The effect of using inflection points for in-depth analysis is that: in determining the feasibility of the clipping path, by counting the total number of inflection points and comparing them with the threshold, the clipping difficulty of the clipping 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 the selection of a path with excessive clipping difficulty, thereby ensuring the feasibility of the operation; In terms of evaluating the difficulty of cutting paths, the inflection point angles are analyzed, and 90 degrees is used as the limit to distinguish between low and high angles of cutting difficulty. By counting the ratio of the number of high angles to the total number and calculating the average of the difference between the high angle and the limit, the high degree of cutting difficulty is obtained, which can more carefully measure the cutting difficulty of the path in terms of angle changes; In terms of the quality of the clipping path, the Gini coefficient is calculated to characterize the uniformity of the inflection point distribution. The closer the Gini coefficient is to 0, the more uniform the inflection point distribution is, and the higher the path quality is, which provides a quantitative indicator for judging the quality of the path. By combining these inflection point-based analysis results with the mean pheromone concentration and length coefficient, the clipping path can be comprehensively and deeply evaluated. Finally, the most suitable optimal clipping path can be selected by calculating the clipping path selection index, which greatly improves the scientificity and accuracy of path selection in the leakage area measurement process, reduces the measurement error caused by unreasonable path, and effectively improves the reliability and practicality of the entire leakage estimation method. The technical solution of this embodiment is as follows: firstly, the transferred image is grayed, the mean and variance of the gradient amplitude of the edge sub-region are calculated, the fuzzy edge region is screened out by the variance threshold, and then a clipping path set is generated based on the ant colony algorithm, and a selection model is constructed by integrating multi-dimensional indicators such as inflection point distribution uniformity, path length, pheromone concentration, etc., and finally the optimal clipping path is determined; By analyzing the clarity of the edge sub-area of ​​the transferred image, the blurred area can be accurately determined, providing a basis for subsequent processing. The ant colony algorithm is used to generate a set of clipping paths, which can explore more paths and increase the possibility of finding a suitable path. When selecting the best clipping path, a comprehensive evaluation of various factors is carried out, fully considering the clipping difficulty and path quality. It can effectively reduce the measurement error caused by edge blur, improve the accuracy of leakage area measurement, and thus improve the reliability of leakage estimation, thereby enhancing the applicability and practicality of the entire measurement method.

[0020] Embodiment 3 Based on the above embodiments, Figure 3 As shown, an embodiment of the present invention provides a leakage point area measurement system for satellite leakage detection and water leakage estimation, which specifically includes: Clarity analysis module: after the ink pad on the plasticine is transferred to the pre-prepared cardboard with uniform texture, the edge sub-region of the transferred image is analyzed for clarity to extract the fuzzy edge sub-region group; Clipping path selection module: Based on the obtained fuzzy edge sub-region group, a clipping path set is generated and the best clipping path is selected.

[0021] In the above embodiments, the description of each embodiment has its own emphasis. For parts that are not described or recorded in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0022] The above formulas are all dimensionless and numerical calculations. The formula is a formula for the most recent real situation obtained by collecting a large amount of data and performing software simulation. The preset parameters in the formula are set by technicians in this field according to actual conditions.

[0023] The above is a detailed description of an embodiment of the present invention, but the content is only a preferred embodiment of the present invention and cannot be considered to limit the scope of implementation of the present invention. All equivalent changes and improvements made within the scope of the present invention should still fall within the scope of the patent coverage 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.

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 as follows: 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 selecting the best clipping path includes: For any clipping path, get all the inflection points on the clipping path; The total number of inflection points is counted and compared 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.

6. A method for measuring the leakage point area for satellite leakage detection and water leakage estimation according to claim 5, characterized in that: The process of selecting the best clipping path also includes: Data analysis was performed on all the optional paths to calculate the inflection point difficulty coefficient, pheromone concentration mean and length coefficient; 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.

7. The method for measuring the leakage point area for satellite leakage detection and water leakage estimation according to claim 6 is characterized in that: The process of obtaining the inflection point difficulty coefficient is as follows: 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; The inflection point difficulty coefficient is obtained by weighted calculation of the proportion of high cutting difficulty angles, high cutting difficulty degree and uniformity value.

8. The method for measuring the leakage point area for satellite leakage detection and water leakage estimation according to claim 7, characterized in that: The process of obtaining the high-difficulty-cutting angle ratio and the high-difficulty-cutting degree is as follows: 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; The inflection point angle corresponding to the angle with high cutting difficulty is extracted, and the difference between the angle and the inflection point angle limit is calculated respectively, and the ratio of the difference and the inflection point angle limit is calculated. Then, the final ratio is averaged to obtain the high degree of cutting difficulty value.

9. The method for measuring the leakage point area for satellite leakage detection and water leakage estimation according to claim 6, 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.

10. The method for measuring the leakage point area for satellite leakage detection and water leakage estimation according to claim 6, characterized in that: The process of obtaining the length coefficient is as follows: The total length of the clipping path is calculated and normalized to obtain the length coefficient.

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