Hydraulic pipeline leakage rate measuring and calculating method and device, electronic equipment and storage medium

Abstract

The invention provides a hydraulic pipeline leakage rate measuring and calculating method and device, electronic equipment and a storage medium. The method comprises the steps that an original hydraulic pipeline image before measuring and calculating and a target hydraulic pipeline image during measuring and calculating are obtained; adjusting the weight of a structure component in a structure similarity algorithm; and calculating to obtain a leakage rate result of the hydraulic pipeline. According to the hydraulic pipeline leakage rate measuring and calculating method and device, the electronic equipment and the storage medium provided by the embodiment of the invention, the leakage rate of the hydraulic pipeline is measured and calculated based on the improved structural similarity algorithm, and the structural information embodied by the positions of the multiple leakage points and the topological adjacency relation between the positions of the leakage points are considered; therefore, the weight of the structural component in the structural similarity algorithm is dynamically adjusted according to the structured information degree of the target hydraulic pipeline image, and a more accurate floor drain rate measurement result is achieved.

Description

Technical Field

[0001] The present application relates to the field of aviation engineering technology, and in particular to a method, device, electronic equipment and storage medium for calculating leakage rate of a hydraulic pipeline. Background Art

[0002] During the maintenance and overhaul of aircraft, it is very important to conduct leak detection on the hydraulic pipeline system to ensure that there are no oil leaks in the pipeline system, which is conducive to ensuring the performance and stability of the aircraft. The performance of large aircraft actuation systems such as hatch opening and closing, landing gear retraction and extension depends on the high-reliability hydraulic pipeline system. Therefore, the sealing test and verification of hydraulic pipelines is a necessary link in the assembly process of large aircraft. However, in the actual assembly process, the location of hydraulic pipeline leakage points and the calculation of oil drop leakage rate are mainly carried out manually, which requires high experience of workers, is time-consuming and labor-intensive, and is easily affected by environmental, vibration and other factors, causing human judgment errors or operational errors, which in turn lead to errors in the hydraulic pipeline detection results, seriously affecting the safety of the aircraft in service and the stability of the actuation system.

[0003] With the innovation of high-resolution motion cameras and the continuous evolution of image processing algorithms, the method of target feature recognition and extraction based on visual images has been continuously applied in structural flaw detection, damage feature value calculation and evaluation, intelligent diagnosis, etc. This method can achieve efficient extraction of target features by giving a filter matrix or setting a feature threshold for the grayscale or RGB three-channel features corresponding to each pixel of the visual image, and will not be affected by the noise and vibration of the complex assembly environment of the production site, and has a broad application prospect in leakage rate measurement. However, the existing image processing algorithms are not specially designed for hydraulic pipeline images, resulting in the use of general image processing algorithms such as peak signal-to-noise ratio and structural similarity to measure the leakage rate of hydraulic pipelines. It is impossible to distinguish the impact of the leakage point located in different parts of the hydraulic pipeline on the measurement result, and it is also impossible to identify the impact of the topological adjacency relationship between multiple leakage points on the measurement result, resulting in inaccurate measurement results. Summary of the invention

[0004] The purpose of the embodiments of the present application is to provide a method, device, electronic device and storage medium for calculating the leakage rate of a hydraulic pipeline.

[0005] In a first aspect, an embodiment of the present invention provides a method for calculating a leakage rate of a hydraulic pipeline, the method comprising:

[0006] respectively obtaining an original hydraulic pipeline image before measurement and a target hydraulic pipeline image during measurement;

[0007] Extracting the oil droplet contours of multiple leak points of the target hydraulic pipeline image, and calculating the multiple leak point positions of the target hydraulic pipeline image according to the oil droplet contours of multiple leak points;

[0008] Determine a structural confidence weight corresponding to the target hydraulic pipeline image according to component information corresponding to each of the multiple leakage point locations and topological adjacency information between the multiple leakage point locations, and adjust a weight of a structural component in a structural similarity algorithm according to the structural confidence weight;

[0009] According to the similarity result obtained by inputting the original hydraulic pipeline image and the target hydraulic pipeline image into the structural similarity algorithm, the total leakage of the hydraulic pipeline is calculated, and then the leakage rate result of the hydraulic pipeline is calculated.

[0010] Optionally, determining the structural confidence weight corresponding to the target hydraulic pipeline image according to the component information corresponding to each of the multiple leakage point positions and the topological adjacency information between the multiple leakage point positions specifically includes:

[0011] Determine the component information corresponding to each leakage point location, and obtain the leakage point weight corresponding to each leakage point location by searching the component information weight table;

[0012] Accumulate the leakage point weights corresponding to the leakage point positions to obtain the total leakage point weight;

[0013] Determine the topological adjacency coefficients corresponding to the multiple leakage point positions according to the proportion of the number of leakage point positions in the maximum leakage point position set in the multiple leakage point positions that are in a topological adjacency relationship;

[0014] According to the total weight of the leakage points and the topological adjacency coefficient, a structural confidence weight corresponding to the target hydraulic pipeline image is obtained.

[0015] Optionally, the component information includes: whether the leakage point is located at the elbow or joint of the hydraulic pipeline, whether the leakage point is located at the valve of the hydraulic pipeline, whether the leakage point is located at the pipe of the hydraulic pipeline, and the diameter of the pipe when the leakage point is located at the pipe of the hydraulic pipeline.

[0016] Optionally, determining the topological adjacency coefficients corresponding to the multiple leakage point positions according to the proportion of the leakage point positions in the multiple leakage point positions that are in a topological adjacency relationship specifically includes:

[0017] A combination of the largest number of leakage point positions is selected from the plurality of leakage point positions, so that a component where any leakage point position in the combination of leakage point positions is located is topologically adjacent to a component where at least one other leakage point position in the combination is located.

[0018] Optionally, the step of calculating the locations of multiple leakage points of the target hydraulic pipeline image according to the multiple leakage point oil droplet contours specifically includes:

[0019] For each oil droplet contour, find the corresponding maximum inscribed circle in the target hydraulic pipeline image; wherein all pixels in the maximum inscribed circle do not overlap with the oil droplet contour pixels, and the maximum inscribed circle has the most adjacent pixels with the oil droplet contour pixels;

[0020] The pixel where the center of the maximum inscribed circle is located is determined as the leakage point position corresponding to the oil droplet contour.

[0021] Optionally, extracting the oil droplet contours of multiple leakage points of the target hydraulic pipeline image specifically includes:

[0022] grayscale and binarize the target hydraulic pipeline image to obtain a processed target hydraulic pipeline image;

[0023] The processed target hydraulic pipeline image is subjected to edge detection using a Sobel operator to obtain the multi-leakage point oil droplet contours of the target hydraulic pipeline image.

[0024] Optionally, the calculating to obtain the leakage rate result of the hydraulic pipeline specifically includes:

[0025] According to the time when the original hydraulic pipeline image and the target hydraulic pipeline image are respectively acquired, a measured time difference is obtained;

[0026] The leakage rate result of the hydraulic pipeline is obtained according to the total leakage of the hydraulic pipeline and the measured time difference.

[0027] In a second aspect, an embodiment of the present invention provides a hydraulic pipeline leakage rate measuring device, the device comprising:

[0028] An image acquisition module, used to respectively acquire an original hydraulic pipeline image before measurement and a target hydraulic pipeline image during measurement;

[0029] A leakage point testing module, used for extracting the multi-leakage point oil droplet contours of the target hydraulic pipeline image, and calculating the multi-leakage point positions of the target hydraulic pipeline image according to the multi-leakage point oil droplet contours;

[0030] A structural component adjustment module, used to determine the structural confidence weight corresponding to the target hydraulic pipeline image according to the component information corresponding to each of the multiple leakage point positions and the topological adjacency information between the multiple leakage point positions, and adjust the weight of the structural component in the structural similarity algorithm according to the structural confidence weight;

[0031] The leakage rate calculation module is used to calculate the total leakage of the hydraulic pipeline according to the similarity result obtained by inputting the original hydraulic pipeline image and the target hydraulic pipeline image into the structural similarity algorithm, and then calculate the leakage rate result of the hydraulic pipeline.

[0032] In a third aspect, an embodiment of the present invention provides an electronic device, characterized in that it includes:

[0033] one or more processors;

[0034] A memory for storing one or more programs;

[0035] When the one or more programs are executed by the one or more processors, the one or more processors execute the method as described in the first aspect.

[0036] In a fourth aspect, an embodiment of the present invention provides a computer-readable storage medium having executable instructions stored thereon, wherein when the executable instructions are executed by a processor, the processor is caused to execute the method described in the first aspect.

[0037] The hydraulic pipeline leakage rate calculation method, device, electronic device and storage medium provided in the embodiments of the present invention calculate the leakage rate of the hydraulic pipeline based on an improved structural similarity algorithm, taking into account the structural information reflected by each of the multiple leakage point positions and the topological adjacency relationship between the leakage point positions, thereby dynamically adjusting the weight of the structural component in the structural similarity algorithm according to the degree of structural information of the target hydraulic pipeline image, thereby achieving a more accurate leakage rate calculation result. BRIEF DESCRIPTION OF THE DRAWINGS

[0038] In order to more clearly illustrate the technical solution of the embodiments of the present application, the drawings required for use in the embodiments of the present application are briefly introduced below.

[0039] Figure 1 A schematic diagram of a flow chart of a method for calculating a hydraulic pipeline leakage rate provided by an embodiment of the present invention;

[0040] Figure 2 A schematic diagram of a flow chart of a structure confidence weight adjustment algorithm provided by an embodiment of the present invention;

[0041] Figure 3 A schematic diagram of the structure of a hydraulic pipeline leakage rate measuring device provided in an embodiment of the present invention;

[0042] Figure 4 A schematic diagram of the structure of an electronic device provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0043] The technical solutions in the embodiments of the present application will be described below in conjunction with the drawings in the embodiments of the present application.

[0044] Similar reference numerals and letters represent similar items in the following drawings, so once an item is defined in one drawing, it does not need to be further defined and explained in subsequent drawings. At the same time, in the description of this application, the terms "first", "second", etc. are only used to distinguish the description and cannot be understood as indicating or implying relative importance.

[0045] During the maintenance and overhaul of aircraft, it is very important to conduct leak detection on the hydraulic pipeline system to ensure that there are no oil leaks in the pipeline system, which is conducive to ensuring the performance and stability of the aircraft. The performance of large aircraft actuation systems such as hatch opening and closing, landing gear retraction and extension depends on the high-reliability hydraulic pipeline system. Therefore, the sealing test and verification of hydraulic pipelines is a necessary link in the assembly process of large aircraft. However, in the actual assembly process, the location of hydraulic pipeline leakage points and the calculation of oil drop leakage rate are mainly carried out manually, which requires high experience of workers, is time-consuming and labor-intensive, and is easily affected by environmental, vibration and other factors, causing human judgment errors or operational errors, which in turn lead to errors in the hydraulic pipeline detection results, seriously affecting the safety of the aircraft in service and the stability of the actuation system.

[0046] With the innovation of high-resolution motion cameras and the continuous evolution of image processing algorithms, the method of target feature recognition and extraction based on visual images has been continuously applied in structural flaw detection, damage feature value calculation and evaluation, intelligent diagnosis, etc. This method can achieve efficient extraction of target features by giving a filter matrix or setting a feature threshold for the grayscale or RGB three-channel features corresponding to each pixel of the visual image, and will not be affected by the noise and vibration of the complex assembly environment of the production site, and has a broad application prospect in leakage rate measurement. However, the existing image processing algorithms are not specially designed for hydraulic pipeline images, resulting in the use of general image processing algorithms such as peak signal-to-noise ratio and structural similarity to measure the leakage rate of hydraulic pipelines. It is impossible to distinguish the impact of the leakage point located in different parts of the hydraulic pipeline on the measurement result, and it is also impossible to identify the impact of the topological adjacency relationship between multiple leakage points on the measurement result, resulting in inaccurate measurement results.

[0047] Based on this, an embodiment of the present invention provides a method for calculating the leakage rate of a hydraulic pipeline. Figure 1 A schematic flow chart of a method for calculating a hydraulic pipeline leakage rate provided in an embodiment of the present invention is shown.

[0048] Step S110, respectively acquiring an original hydraulic pipeline image before measurement and a target hydraulic pipeline image during measurement.

[0049] The embodiments of the present invention are applied to the detection of oil leakage in hydraulic pipelines in the field of aviation engineering. The hydraulic system is an important part of an aircraft, responsible for controlling key components such as the aircraft's landing gear, flaps, and rudder. Any slight leakage in the hydraulic pipeline may cause the system pressure to drop, thereby affecting the normal operation of these components and even endangering flight safety.

[0050] Leak rate data is one of the important indicators for evaluating the status of hydraulic systems. By comparing the leak rate data at different time points, we can understand whether the sealing performance of the system is stable and whether there is a deterioration trend; based on the leak rate data, a reasonable maintenance plan can be formulated. For pipelines or components with high leak rates, repair or replacement can be arranged first to ensure the normal operation of the system. By analyzing the leak rate data, the root cause of the leakage can be found, such as unreasonable pipeline design, improper material selection, etc. This information can provide an important reference for optimizing system design and reducing the occurrence of similar problems in the future.

[0051] The embodiment of the present invention uses an image processing method to calculate the leakage rate of the hydraulic pipeline, and needs to obtain two images of the target area to be measured at different times. The time when the first image is captured is the first moment before the measurement, and it is used as the original hydraulic pipeline image; the time when the second image is captured is the second moment during the measurement, and it is used as the target hydraulic pipeline image. When capturing the two images, the target area and related equipment parameters captured by the acquisition device are exactly the same. The target area includes the global or partial key areas of the hydraulic pipeline system. The acquisition device can be an image acquisition device such as a camera in the safety monitoring system of aviation machinery. The specific model can be formulated according to actual needs, and the embodiment of the present invention does not make specific limitations.

[0052] There is a time difference between the first time and the second time when the original hydraulic pipeline image and the target hydraulic pipeline image are respectively acquired, and the time difference can be set according to an empirical value, such as 15 or 30 seconds.

[0053] Step S120 , extracting the oil droplet contours of multiple leak points of the target hydraulic pipeline image, and calculating the positions of multiple leak points of the target hydraulic pipeline image according to the oil droplet contours of multiple leak points.

[0054] The embodiment of the present invention does not directly analyze the image through the image processing algorithm to estimate the leakage rate of the hydraulic pipeline, but is based on the fact that the oil drop leakage of the hydraulic pipeline is usually manifested in the form of point leakage, so the leakage point position is first located in the image, and then the leakage point position is analyzed to calculate the leakage rate result of the hydraulic pipeline. If there are multiple leakage points in different positions, it is necessary to locate the positions of multiple leakage points in the image. The multiple leakage points in the embodiment of the present invention can refer to the situation where there are multiple leakage points, or it can refer to the situation where there is only one leakage point.

[0055] When locating the positions of multiple leak points, this step mainly analyzes the target hydraulic pipeline image. Through digital image processing technology, the contours of the oil droplets at the multiple leak points are first extracted, and then the positions of the multiple leak points in the target hydraulic pipeline image are calculated based on the contours of the oil droplets at the multiple leak points.

[0056] When extracting the contours of oil droplets at multiple leakage points, it is necessary to perform grayscale processing on the acquired target hydraulic pipeline image. A more reasonable grayscale image Gray(x, y) can be obtained by weighted averaging the RGB three-channel components R(x, y), G(x, y), and B(x, y) according to the following formula.

[0057] Gray(x,y)=0.299×R(x,y)+0.578×G(x,y)+0.114×B(x,y)

[0058] The grayscale image is then binarized using an adaptive threshold strategy, that is, a local threshold T(x, y) is calculated for each pixel or neighborhood in the image for binarization. The grayscale image is converted into a black-and-white binary image dst(x, y) containing only two pixel values ​​according to the following formula.

[0059]

[0060] Then the Sobel operator is used to perform edge detection on the black and white binary image. The Sobel operator contains two sets of 3×3 matrices, which are horizontal and vertical templates respectively. By performing a planar convolution with the image, the horizontal and vertical brightness difference approximations can be obtained respectively, so as to obtain the position and intensity of the edge in the image, obtain accurate edge information, and then extract the contours of oil droplets at multiple leakage points.

[0061] Detection of horizontal template

[0062]

[0063] Detect templates in the vertical direction (along the longitudinal direction)

[0064]

[0065] The approximate horizontal and vertical gradients of each pixel in the image can be combined using the following formula to calculate the magnitude of the gradient.

[0066]

[0067] Then the gradient direction can be calculated using the following formula.

[0068]

[0069] After extracting the multiple leak point oil droplet contours of the target hydraulic pipeline image, for each oil droplet contour, find the corresponding maximum inscribed circle in the target hydraulic pipeline image. The maximum inscribed circle means that all pixels within its range do not overlap with the oil droplet contour pixels, and the maximum inscribed circle has the most adjacent pixels with the oil droplet contour pixels. The method for determining the maximum inscribed circle is to traverse each extracted oil droplet contour and calculate the distance value from each pixel point in the contour to the contour; wherein the pixel with the largest distance value is the pixel where the center of the maximum inscribed circle is located, and is confirmed as the leak point position corresponding to the corresponding oil droplet contour. When the target hydraulic pipeline image has multiple leak point oil droplet contours, multiple leak point positions can be confirmed accordingly.

[0070] Step S130, determining the structural confidence weight corresponding to the target hydraulic pipeline image according to the component information corresponding to each of the multiple leakage point positions and the topological adjacency information between the multiple leakage point positions, and adjusting the weight of the structural component in the structural similarity algorithm according to the structural confidence weight.

[0071] The embodiment of the present invention ultimately uses a structural similarity algorithm to measure the leakage rate of the hydraulic pipeline. However, although the traditional structural similarity algorithm not only counts the brightness and contrast features in the image, but also counts the structural information to evaluate the similarity of the image, the subtle differences in the complex structure of the image may be ignored by the algorithm, resulting in inaccurate similarity evaluation, and the oil drop leakage of the hydraulic pipeline happens to belong to the complex structure and subtle features.

[0072] In addition, traditional structural similarity algorithms mainly focus on low-level visual features of images, but lack understanding of the semantic content of images. In the scenario of the embodiment of the present invention, traditional structural similarity algorithms cannot understand in which component of the hydraulic pipeline system the leak is located, and then analyze the impact of the leak on the structural information, nor can they understand the impact of the relationship between multiple leaks on the structural information. The ideal structural similarity algorithm should dynamically adjust the weight of the structural component among the brightness component, contrast component, and structural component in the structural similarity algorithm according to the importance of the structural information. Static weight values ​​that are too large or too small will affect the accuracy of the structural similarity algorithm.

[0073] In this step, each leak point located belongs to a specific component of the hydraulic pipeline system: such as pipelines, joints, elbows, valves, etc., among which valves have the least structural information, followed by joints and elbows, and pipeline components have the most structural information; similarly, for pipelines, the smaller the diameter, the higher the structural information. Since the structure of the hydraulic pipeline system to be measured is known, the component information where the leak point is located can be obtained based on a simple image recognition method. Therefore, the component information in this step may include: whether the leak point is located at the elbow or joint of the hydraulic pipeline, whether the leak point is located at the valve of the hydraulic pipeline, whether the leak point is located at the pipe of the hydraulic pipeline, and when the leak point is located at the pipe of the hydraulic pipeline, the diameter of the pipe.

[0074] In addition, different components in the hydraulic pipeline system have a topological connection relationship. For example, pipeline A and valve X are connected, that is, they have a topological adjacency relationship. At this time, if leakage point 1 corresponds to pipeline A and leakage point 2 corresponds to valve X, then leakage point 1 and leakage point 2 are considered to have a topological adjacency relationship. The higher the degree of topological adjacency between multiple leakage points in the hydraulic pipeline system, the higher the proportion of structured information in the structural similarity algorithm.

[0075] In this step, it is necessary to determine the structural confidence weight corresponding to the target hydraulic pipeline image according to the component information corresponding to each of the multiple leakage point locations and the topological adjacency information between the multiple leakage point locations. Figure 2 A schematic flow chart of a structure confidence weight adjustment algorithm provided in an embodiment of the present invention is shown, which specifically includes the following steps S131 to S134.

[0076] Step S131, determining the component information corresponding to each leakage point position, and obtaining the leakage point weight corresponding to each leakage point position by searching the component information weight table.

[0077] Step S132, accumulating the leakage point weights corresponding to the leakage point positions to obtain the total leakage point weight.

[0078] Step S133, determining the topological adjacency coefficients corresponding to the multiple leakage point positions according to the proportion of the number of leakage point positions in the maximum leakage point position set that is in a topological adjacency relationship among the multiple leakage point positions.

[0079] Step S134: obtaining a structural confidence weight corresponding to the target hydraulic pipeline image according to the total weight of the leakage points and the topological adjacency coefficient.

[0080] In the embodiment of the present invention, since the structure of the hydraulic pipeline system to be measured is known, the component information of the leakage point can be obtained according to a simple image recognition method, and the leakage point weight corresponding to each component information can be preset according to the historical experience value and pre-stored in a component information weight table. The component information weight table can store, for example, the following information: pipeline 0-10mm, weight 0.5; pipeline 10-20mm, weight 0.4; pipeline 20-30mm, weight 0.3; joint or elbow, weight 0.2; valve, weight 0.1. The above data is only exemplary, and in different actual hydraulic pipeline systems, users can customize the preset weight values.

[0081] After obtaining multiple leakage point weights for multiple leakage point positions in the target hydraulic pipeline image, the total leakage point weight can be obtained by cumulative calculation, which reflects the degree of structural information reflected by the positions of each leakage point. In addition to the degree of structural information reflected by each leakage point position, the degree of structural information reflected by the relationship between the leakage point positions needs to be obtained through the topological adjacency relationship between the leakage point positions.

[0082] The embodiment of the present invention needs to find the largest set of leakage point locations in a topologically adjacent relationship among multiple leakage point locations. In the embodiment of the present invention, if the components where two leakage points are located are the same and connected, then the two leakage points are considered to have a topologically adjacent relationship; for a set of three or more leakage points, if any leakage point in the set has a topologically adjacent relationship with another leakage point in the set, then the leakage points in the set are considered to have a topologically adjacent relationship. At this time, it is necessary to find the largest set of leakage point locations in a topologically adjacent relationship. For example, for the four located leakage points 1 to 4, the component where leakage points 1 and 2 are located is pipeline A, the component where leakage point 3 is located is elbow M, and the component where leakage point 4 is located is valve X, wherein pipeline A is connected to elbow M, and valve X is connected to neither pipeline A nor elbow M. Then, the maximum leakage point position set in a topological adjacency relationship is the set composed of leakage points 1 to 3, which is the set with the highest proportion of leakage point positions in the maximum leakage point position set in a topological adjacency relationship among multiple leakage point positions 1 to 4, accounting for 75%, so the topological adjacency coefficient corresponding to the multiple leakage point positions is determined to be 0.75.

[0083] After obtaining the total weight of the leakage point and the topological adjacency coefficient, it is necessary to calculate the structural confidence weight corresponding to the target hydraulic pipeline image. The calculation formula in the embodiment of the present invention is: structural confidence weight = total weight of leakage point × (1 + topological adjacency coefficient). This formula reflects that the higher the degree of structural information reflected by each leakage point position, or the higher the degree of structural information reflected by the relationship between the leakage point positions, the higher the calculated structural confidence weight.

[0084] After the structural confidence weight is calculated in steps S131 to S134, the weight of the structural component in the structural similarity algorithm needs to be adjusted according to the structural confidence weight. The structural similarity algorithm generally includes three parts: brightness component, contrast component and structural component. The importance of each of the three parts depends on the respective weight value to be adjusted. Experimental data show that in the hydraulic pipeline image of the embodiment of the present invention, the degree of structured signal has a greater disturbance on the accuracy of the structural similarity algorithm. Therefore, it is necessary to dynamically adjust the weight of the structural component in the structural similarity algorithm according to the degree of structured information of different target hydraulic pipeline images as in the embodiment of the present invention.

[0085] The structural similarity SSIM(x, y) generally includes a brightness component 1(x, y), a contrast component c(x, y) and a structure component s(x, y). The corresponding brightness component weight, contrast component weight and structure component weight satisfy α>0, β>0 and γ>0 respectively, and are calculated according to the following formula.

[0086] SSIM(x,y)=(1(x,y)) α (c(x,y)) β (s(x,y)) γ

[0087] Generally speaking, the default values ​​of α, β, and γ in the structural similarity calculation formula are all 1. When adjusting the structural component weight γ, in order to prevent overfitting of the structural information, the upper limit of the γ adjustment can be preset, for example, the upper limit is 3, that is, the value range of γ adjustment is [1, 3]. At this time, the formula for adjusting the weight of the structural component in the structural similarity algorithm according to the structural confidence weight m can be obtained by comparing the structural confidence weight m with the historical average structural confidence weight n. The historical average structural confidence is the average value of the structural confidence obtained in the process of all hydraulic pipeline images processed in history, which is a statistical data. Therefore, the calculation formula for adjusting γ can be as follows:

[0088] γ=2+(mn) / n

[0089] Step S140, calculating the total leakage of the hydraulic pipeline according to the similarity result obtained by inputting the original hydraulic pipeline image and the target hydraulic pipeline image into the structural similarity algorithm, and then calculating the leakage rate result of the hydraulic pipeline.

[0090] After adjusting the weight γ of the structural component in the structural similarity algorithm, the original hydraulic pipeline image and the target hydraulic pipeline image are input into the structural similarity algorithm to obtain the similarity result of the original hydraulic pipeline image and the target hydraulic pipeline image. According to the similarity result, the total leakage of the hydraulic pipeline can be calculated. An example of the calculation process is as follows.

[0091] Determine whether the real-time image SSIM (x, y) is ≥ 0.95. If so, this image indicates that there is no oil droplet leakage;

[0092] If not, then determine whether SSIM(x, y)≥0.8. If so, it means that the SSIM(x, y)∈[0.8, 0.95) of this image indicates that there is only one drop of oil leakage, and the number of oil drop leakage statistics increases by one;

[0093] If not, then determine whether SSIM(x, y) ≥ 0.7. If so, it means that SSIM(x, y)∈[0.7, 0.8) of this image indicates that there are two drops of oil leaking, and the number of oil leaking statistics is increased by two;

[0094] If not, it means that this image SSIM(x, y)∈[0, 0.7) indicates that three drops of oil have leaked, and the number of oil drop leaks is increased by three.

[0095] After obtaining the number of leaked oil droplets used to characterize the total leakage of the hydraulic pipeline, the measured time difference is obtained according to the moments when the original hydraulic pipeline image and the target hydraulic pipeline image are respectively acquired; and the leakage rate result of the hydraulic pipeline is obtained according to the total leakage of the hydraulic pipeline and the measured time difference.

[0096] The leakage rate result V is calculated according to the following formula, where n is the total leakage volume and T is the duration of oil drop leakage.

[0097] The hydraulic pipeline leakage rate calculation method provided in an embodiment of the present invention calculates the leakage rate of the hydraulic pipeline based on an improved structural similarity algorithm, taking into account the structural information reflected by each of the multiple leakage point positions and the topological adjacency relationship between the leakage point positions, thereby dynamically adjusting the weight of the structural component in the structural similarity algorithm according to the degree of structural information of the target hydraulic pipeline image, thereby achieving a more accurate leakage rate calculation result.

[0098] Based on any of the above embodiments, Figure 3 The structural schematic diagram of the hydraulic pipeline leakage rate measuring device provided by the embodiment of the present invention is shown, and the specific contents are as follows:

[0099] An image acquisition module 310 is used to respectively acquire an original hydraulic pipeline image before measurement and a target hydraulic pipeline image during measurement;

[0100] A leakage point testing module 320 is used to extract the multi-leakage point oil droplet contours of the target hydraulic pipeline image, and calculate the multi-leakage point positions of the target hydraulic pipeline image according to the multi-leakage point oil droplet contours;

[0101] A structural component adjustment module 330, for determining a structural confidence weight corresponding to the target hydraulic pipeline image according to component information corresponding to each of the multiple leakage point locations and topological adjacency information between the multiple leakage point locations, and adjusting a weight of a structural component in a structural similarity algorithm according to the structural confidence weight;

[0102] The leakage rate calculation module 340 is used to calculate the total leakage of the hydraulic pipeline according to the similarity result obtained by inputting the original hydraulic pipeline image and the target hydraulic pipeline image into the structural similarity algorithm, and then calculate the leakage rate result of the hydraulic pipeline.

[0103] The hydraulic pipeline leakage rate calculation device provided in an embodiment of the present invention calculates the leakage rate of the hydraulic pipeline based on an improved structural similarity algorithm, taking into account the structural information reflected by each of the multiple leakage point positions and the topological adjacency relationship between the leakage point positions, thereby dynamically adjusting the weight of the structural component in the structural similarity algorithm according to the degree of structural information of the target hydraulic pipeline image, thereby achieving a more accurate leakage rate calculation result.

[0104] Based on any of the above embodiments, Figure 4 The physical structure diagram of the electronic device provided by the embodiment of the present invention is shown, and the electronic device may include: a processor (processor) 410, a communication interface (CommunicationsInterface) 420, a memory (memory) 430 and a communication bus 440, wherein the processor 410, the communication interface 420, and the memory 430 communicate with each other through the communication bus 440. The processor 410 can call the logic instructions in the memory 430 to execute the following method:

[0105] respectively obtaining an original hydraulic pipeline image before measurement and a target hydraulic pipeline image during measurement;

[0106] Extracting the oil droplet contours of multiple leak points of the target hydraulic pipeline image, and calculating the positions of multiple leak points of the target hydraulic pipeline image according to the oil droplet contours of multiple leak points;

[0107] Determine a structural confidence weight corresponding to the target hydraulic pipeline image according to component information corresponding to each of the multiple leakage point locations and topological adjacency information between the multiple leakage point locations, and adjust a weight of a structural component in a structural similarity algorithm according to the structural confidence weight;

[0108] According to the similarity result obtained by inputting the original hydraulic pipeline image and the target hydraulic pipeline image into the structural similarity algorithm, the total leakage of the hydraulic pipeline is calculated, and then the leakage rate result of the hydraulic pipeline is calculated.

[0109] In addition, the logic instructions in the above-mentioned memory 430 can be implemented in the form of a software functional unit and can be stored in a computer-readable storage medium when it is sold or used as an independent product. Based on such an understanding, the technical solution of the embodiment of the present invention is essentially or the part that contributes to the prior art or the part of the technical solution can be embodied in the form of a software product, and the computer software product is stored in a storage medium, including a number of instructions to enable a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the method described in the embodiment of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk and other media that can store program codes.

[0110] On the other hand, an embodiment of the present invention further provides a non-transitory computer-readable storage medium on which a computer program is stored. When the computer program is executed by a processor, the method provided in each of the above embodiments is implemented, for example, including:

[0111] respectively obtaining an original hydraulic pipeline image before measurement and a target hydraulic pipeline image during measurement;

[0112] Extracting the oil droplet contours of multiple leak points of the target hydraulic pipeline image, and calculating the multiple leak point positions of the target hydraulic pipeline image according to the oil droplet contours of multiple leak points;

[0113] Determine a structural confidence weight corresponding to the target hydraulic pipeline image according to component information corresponding to each of the multiple leakage point locations and topological adjacency information between the multiple leakage point locations, and adjust a weight of a structural component in a structural similarity algorithm according to the structural confidence weight;

[0114] According to the similarity result obtained by inputting the original hydraulic pipeline image and the target hydraulic pipeline image into the structural similarity algorithm, the total leakage of the hydraulic pipeline is calculated, and then the leakage rate result of the hydraulic pipeline is calculated.

[0115] The device embodiments described above are merely illustrative, wherein the units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they may be located in one place, or they may be distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the scheme of this embodiment. Ordinary technicians in this field can understand and implement it without paying creative labor.

[0116] Through the description of the above implementation methods, those skilled in the art can clearly understand that each implementation method can be implemented by means of software plus a necessary general hardware platform, and of course, it can also be implemented by hardware. Based on this understanding, the above technical solution is essentially or the part that contributes to the prior art can be embodied in the form of a software product, and the computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, a disk, an optical disk, etc., including a number of instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to execute the methods described in each embodiment or some parts of the embodiments.

[0117] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for calculating leakage rate of a hydraulic pipeline, characterized in that: The method comprises: respectively obtaining an original hydraulic pipeline image before measurement and a target hydraulic pipeline image during measurement; Extracting the oil droplet contours of multiple leak points of the target hydraulic pipeline image, and calculating the positions of multiple leak points of the target hydraulic pipeline image according to the oil droplet contours of multiple leak points; Determine a structural confidence weight corresponding to the target hydraulic pipeline image according to component information corresponding to each of the multiple leakage point locations and topological adjacency information between the multiple leakage point locations, and adjust a weight of a structural component in a structural similarity algorithm according to the structural confidence weight; According to the similarity result obtained by inputting the original hydraulic pipeline image and the target hydraulic pipeline image into the structural similarity algorithm, the total leakage of the hydraulic pipeline is calculated, and then the leakage rate result of the hydraulic pipeline is calculated.

2. The method for calculating the leakage rate of a hydraulic pipeline according to claim 1, characterized in that: The determining, according to the component information corresponding to each of the multiple leakage point positions and the topological adjacency information between the multiple leakage point positions, the structural confidence weight corresponding to the target hydraulic pipeline image specifically includes: Determine the component information corresponding to each leakage point location, and obtain the leakage point weight corresponding to each leakage point location by searching the component information weight table; Accumulate the leakage point weights corresponding to the leakage point positions to obtain the total leakage point weight; Determine the topological adjacency coefficients corresponding to the multiple leakage point positions according to the proportion of the number of leakage point positions in the maximum leakage point position set in the multiple leakage point positions that are in a topological adjacency relationship; According to the total weight of the leakage points and the topological adjacency coefficient, a structural confidence weight corresponding to the target hydraulic pipeline image is obtained.

3. The method for calculating the leakage rate of a hydraulic pipeline according to claim 2, characterized in that: The component information includes: whether the leakage point is located at an elbow or joint of the hydraulic pipeline, whether the leakage point is located at a valve of the hydraulic pipeline, whether the leakage point is located at a pipe of the hydraulic pipeline, and the diameter of the pipe when the leakage point is located at the pipe of the hydraulic pipeline.

4. The method for calculating the leakage rate of a hydraulic pipeline according to claim 2, characterized in that: Determining the topological adjacency coefficients corresponding to the multiple leakage point positions according to the proportion of the leakage point positions in the multiple leakage point positions that are in a topological adjacency relationship specifically includes: A combination of the largest number of leakage point positions is selected from the plurality of leakage point positions, so that a component where any leakage point position in the combination of leakage point positions is located is topologically adjacent to a component where at least one other leakage point position in the combination is located.

5. The method for calculating the leakage rate of a hydraulic pipeline according to claim 1, characterized in that: The step of calculating the positions of multiple leakage points of the target hydraulic pipeline image according to the multiple leakage point oil droplet contours specifically includes: For each oil droplet contour, find the corresponding maximum inscribed circle in the target hydraulic pipeline image; wherein all pixels in the maximum inscribed circle do not overlap with the oil droplet contour pixels, and the maximum inscribed circle has the most adjacent pixels with the oil droplet contour pixels; The pixel where the center of the maximum inscribed circle is located is determined as the leakage point position corresponding to the oil droplet contour.

6. The method for calculating the leakage rate of a hydraulic pipeline according to claim 1, characterized in that: The step of extracting the oil droplet contours of multiple leakage points of the target hydraulic pipeline image specifically includes: grayscale and binarize the target hydraulic pipeline image to obtain a processed target hydraulic pipeline image; The processed target hydraulic pipeline image is subjected to edge detection using a Sobel operator to obtain the multi-leakage point oil droplet contours of the target hydraulic pipeline image.

7. The method for calculating the leakage rate of a hydraulic pipeline according to claim 1, characterized in that: The calculation to obtain the leakage rate result of the hydraulic pipeline specifically includes: According to the time when the original hydraulic pipeline image and the target hydraulic pipeline image are respectively acquired, a measured time difference is obtained; The leakage rate result of the hydraulic pipeline is obtained according to the total leakage of the hydraulic pipeline and the measured time difference.

8. A hydraulic pipeline leakage rate measuring device, characterized in that: The device comprises: An image acquisition module, used to respectively acquire an original hydraulic pipeline image before measurement and a target hydraulic pipeline image during measurement; A leakage point testing module, used for extracting the multi-leakage point oil droplet contours of the target hydraulic pipeline image, and calculating the multi-leakage point positions of the target hydraulic pipeline image according to the multi-leakage point oil droplet contours; A structural component adjustment module, used to determine the structural confidence weight corresponding to the target hydraulic pipeline image according to the component information corresponding to each of the multiple leakage point positions and the topological adjacency information between the multiple leakage point positions, and adjust the weight of the structural component in the structural similarity algorithm according to the structural confidence weight; The leakage rate calculation module is used to calculate the total leakage of the hydraulic pipeline according to the similarity result obtained by inputting the original hydraulic pipeline image and the target hydraulic pipeline image into the structural similarity algorithm, and then calculate the leakage rate result of the hydraulic pipeline.

9. An electronic device, characterized in that: include: one or more processors; A memory for storing one or more programs; When the one or more programs are executed by the one or more processors, the one or more processors execute the method as claimed in any one of claims 1 to 7.

10. A computer-readable storage medium having executable instructions stored thereon, characterized in that: When the executable instructions are executed by a processor, the processor executes the method according to any one of claims 1 to 7.

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