Method and device for detecting leaks in a pipeline based on radar remote sensing

Abstract

The application provides a pipeline leakage point detection method and device based on radar remote sensing, and relates to the field of data processing. The method comprises the following steps: acquiring first radar images of a target pipeline in two time phases before and after by using a synthetic aperture radar; detecting water bodies of the pipeline in the first radar images by using dielectric properties and polarization properties of radar remote sensing of different water sources to obtain an initial detection result; performing deformation detection on the two first radar images based on a differential interferometric measurement technology to obtain a deformation detection result; determining change information corresponding to the first radar images in the two time phases based on a fitting relationship between the deformation detection result and water content; performing screening on the initial detection result based on the change information to obtain a screened detection result; and inputting the screened detection result into a pre-trained network model to output a leakage point detection result. Based on this, the application performs multi-dimensional leakage point detection on the pipeline, thereby improving the detection accuracy.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of data processing, and in particular to a pipeline leak detection method and device based on radar remote sensing. BACKGROUND

[0002] With the continuous updating of SAR (Synthetic Aperture Radar) technology, SAR has realized multi-field application, and one of the application fields at the present stage is SAR-based water leakage detection.

[0003] However, the SAR-based water leakage detection at the present stage is mainly completed by using the underground intensity information or polarization information obtained by SAR, and the accuracy is low. SUMMARY

[0004] Therefore, the present application provides a pipeline leak detection method and device based on radar remote sensing, which is used to improve the current situation that the detection is completed by using the underground intensity information or polarization information obtained by SAR, and the accuracy is low.

[0005] In a first aspect, an embodiment of the present application provides a pipeline leak detection method based on radar remote sensing, comprising:

[0006] Based on synthetic aperture radar, first radar images of two time phases of a target pipeline are obtained;

[0007] Based on the dielectric and polarization characteristics of radar remote sensing of different water sources, leak detection is performed on the first radar images to obtain an initial detection result;

[0008] Based on the differential interferometric measurement technology, deformation analysis is performed on the first radar images of the two time phases to obtain a deformation detection result;

[0009] Based on the fitting relationship between the deformation detection result and the water content, change information corresponding to the first radar images of the two time phases is determined;

[0010] Based on the change information, the initial detection result is screened to obtain a screened detection result;

[0011] The screened detection result is input into a pre-trained network model to obtain a leak detection result of the target pipeline, wherein the network model is obtained by pre-acquiring a plurality of screened detection result samples and performing model training using the plurality of screened detection result samples.

[0012] Optionally, in an embodiment of the present application, the method for leak detection based on the dielectric and polarization characteristics of radar remote sensing of different water sources includes:

[0013] Based on the dielectric properties of different water sources, the first radar image is subjected to leak point detection to obtain a first detection result;

[0014] Based on the polarization properties of different water sources, the first radar image is subjected to leak point detection to obtain a second detection result;

[0015] Based on the intersection of the first detection result and the second detection result, an initial detection result is obtained.

[0016] Optionally, in a feasible manner provided by the embodiment of the present application, the fitting relationship between the deformation detection result and the water content is obtained in advance, and the method further comprises:

[0017] Based on the synthetic aperture radar, a plurality of second radar images are obtained, wherein the plurality of second radar images correspond to the same detection target, and the plurality of second radar images are different in time phase;

[0018] The water content corresponding to each of the second radar images is determined;

[0019] Based on the differential interference measurement technology, deformation analysis is performed on each of the second radar images to obtain a deformation variable corresponding to each of the second radar images;

[0020] The water content and the deformation variable of each of the second radar images are fitted to obtain the fitting relationship.

[0021] Optionally, in a feasible manner provided by the embodiment of the present application, the first radar image of the target pipeline in the two time phases is obtained based on the synthetic aperture radar, which comprises:

[0022] Based on the synthetic aperture radar, the original radar image of the target pipeline in the two time phases is obtained;

[0023] Radiometric calibration and image registration are performed on the original radar image to obtain a calibrated radar image;

[0024] Based on a filtering algorithm, noise reduction processing is performed on the calibrated radar image to obtain the first radar image.

[0025] Optionally, in a feasible manner provided by the embodiment of the present application, the filtering algorithm is any one of Lee filtering algorithm, delicate Lee algorithm, Lee Sigma filtering algorithm, median filtering algorithm and Frost filtering algorithm.

[0026] In a second aspect, the present application provides a pipeline leak point detection device based on radar remote sensing, comprising:

[0027] An acquisition module is configured to obtain, based on a synthetic aperture radar, a first radar image of a target pipeline in two time phases.

[0028] The first detection module is configured to perform leak detection on the first radar image based on dielectric properties and polarization properties of different water sources, and obtain an initial detection result.

[0029] The second detection module is configured to perform deformation analysis on the two time-phase first radar images based on a differential interference measurement technique, and obtain a deformation detection result.

[0030] The determination module is configured to determine change information corresponding to the two time-phase first radar images based on a fitting relationship between the deformation detection result and water content.

[0031] The screening module is configured to screen the initial detection result based on the change information, and obtain a screened detection result.

[0032] The result output module is configured to input the screened detection result into a pre-trained network model, and obtain a leak detection result of the target pipeline, wherein the network model is obtained by pre-acquiring a plurality of screened detection result samples and performing model training on the plurality of screened detection result samples.

[0033] Optionally, in an available manner provided by the embodiment of the present application, the first detection module comprises:

[0034] The leak detection submodule is configured to perform leak detection on the first radar image based on dielectric properties of different water sources, and obtain a first detection result.

[0035] The polarization detection submodule is configured to perform leak detection on the first radar image based on polarization properties of different water sources, and obtain a second detection result.

[0036] The result obtaining submodule is configured to obtain an initial detection result based on an intersection of the first detection result and the second detection result.

[0037] Optionally, in an available manner provided by the embodiment of the present application, the fitting relationship between the deformation detection result and the water content is obtained by pre-acquisition, and the device further comprises:

[0038] The image acquisition module is configured to acquire a plurality of second radar images based on the synthetic aperture radar, wherein the plurality of second radar images correspond to the same detection target, and the plurality of second radar images are different in time phase.

[0039] The water content determination module is configured to determine water content corresponding to each of the second radar images.

[0040] a deformation variable acquisition module, configured to perform deformation analysis on each of the second radar images based on a differential interference measurement technique to obtain a deformation variable corresponding to each of the second radar images;

[0041] a fitting module, configured to fit the water content and the deformation variable of each of the second radar images to obtain the fitting relationship.

[0042] Optionally, in an available manner provided by the embodiment of the present application, the acquisition module comprises:

[0043] an original image acquisition sub-module, configured to acquire original radar images of the target pipeline at two time phases before and after based on a synthetic aperture radar;

[0044] a calibration sub-module, configured to perform radiation scaling and image registration on the original radar images to obtain calibrated radar images;

[0045] a filtering sub-module, configured to perform noise reduction processing on the calibrated radar images based on a filtering algorithm to obtain first radar images.

[0046] Optionally, in an available manner provided by the embodiment of the present application, the filtering algorithm is any one of Lee filtering algorithm, delicate Lee algorithm, Lee Sigma filtering algorithm, median filtering algorithm and Frost filtering algorithm.

[0047] In the pipeline leak point detection method based on radar remote sensing provided by the present application, first, the synthetic aperture radar is used to acquire first radar images of the target pipeline at two time phases before and after; then, the water body in the pipeline in the first radar images is detected based on prior knowledge, i.e., radar remote sensing dielectric properties and polarization properties of different water sources, so as to obtain an initial detection result; subsequently, deformation detection is performed on the two first radar images based on a differential interference measurement technique, so as to obtain a deformation detection result; then, based on the fitting relationship between the deformation detection result and the water content obtained in advance, the water content change corresponding to the deformation detection result, i.e., the change information corresponding to the two time phases of the first radar images, is determined; after that, the initial detection result is subjected to secondary screening based on the change information, so as to obtain a screened detection result; finally, the screened detection result is input into a network model trained in advance, so that the network model performs high-precision identification, and then outputs a leak point detection result. Based on this, the present application performs multi-dimensional leak point detection on the pipeline based on the water content change corresponding to the water source type, radar remote sensing dielectric properties, polarization properties and phase information, thereby avoiding the false detection possibility caused by using single-dimensional information; and the embodiment of the present application further performs secondary screening / detection based on the network model, thereby further improving the accuracy of the leak point detection result. BRIEF DESCRIPTION OF DRAWINGS

[0048] In order to more clearly illustrate the technical solutions of the present application, the following will briefly introduce the drawings needed to be used in the embodiments. It should be understood that the following drawings only show some embodiments of the present application, and therefore should not be regarded as limiting the protection scope of the present application. In the various drawings, similar components are denoted by similar reference numerals.

[0049] Figure 1 A flowchart of a first pipeline leak detection method based on radar remote sensing provided by the embodiment of the present application is shown;

[0050] Figure 2 A flowchart of a second pipeline leak detection method based on radar remote sensing provided by the embodiment of the present application is shown;

[0051] Figure 3 A flowchart of a third pipeline leak detection method based on radar remote sensing provided by the embodiment of the present application is shown;

[0052] Figure 4 A structural diagram of a pipeline leak detection device based on radar remote sensing provided by the embodiment of the present application is shown. DETAILED DESCRIPTION

[0053] The technical solutions in the embodiments of the present application will be described in detail below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only some of the embodiments of the present application, but not all the embodiments.

[0054] The components of the embodiments of the present application generally described and shown in the drawings herein can be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of the present application provided in the drawings is not intended to limit the scope of the claimed present application, but only represents selected embodiments of the present application. Based on the embodiments of the present application, all other embodiments obtained by those skilled in the art without creative labor are within the scope of protection of the present application.

[0055] In the following, the terms "include", "have", and their synonymous words used in various embodiments of the present application are only intended to represent a specific feature, number, step, operation, element, component, or combination of the foregoing, and should not be understood as first excluding the presence or adding the possibility of one or more other features, numbers, steps, operations, elements, components, or combinations of the foregoing.

[0056] In addition, the terms "first", "second", "third", and the like are only used to distinguish the description, and cannot be understood as indicating or implying relative importance.

[0057] Unless otherwise defined, all terms (including technical and scientific terms) used herein have the same meaning as commonly understood by one of ordinary skill in the art to which various embodiments of the present application belong. It will be further understood that terms, such as those defined in commonly used dictionaries, should be interpreted as having a meaning that is consistent with their meaning in the context of the relevant art and will not be interpreted in an idealized or overly formal sense unless expressly so defined in various embodiments of the present application.

[0058] Embodiment 1

[0059] Please refer to Figure 1 , which shows a flowchart of a first pipeline leak detection method based on radar remote sensing provided by an embodiment of the present application. The pipeline leak detection method based on radar remote sensing provided by the embodiment of the present application comprises the following steps.

[0060] In step S110, first radar images of the target pipeline in two time phases before and after are acquired based on a synthetic aperture radar.

[0061] That is, the target pipeline below the ground is remotely sensed and detected by the synthetic aperture radar in the embodiment of the present application, so as to acquire the echo information of the target pipeline below the ground, i.e., the radar images.

[0062] It can be understood that the synthetic aperture radar has the characteristics of high-resolution imaging and can effectively penetrate the ground cover to detect the target below the ground.

[0063] In addition, it should be noted that the target pipeline in the embodiment of the present application refers to a pipeline system or a pipeline network.

[0064] In addition, it can also be understood that there may be speckle noise and other noise when the synthetic aperture radar is imaged, and such noise will affect the phase analysis. Therefore, in order to improve the leak detection accuracy, in one feasible manner provided by the embodiment of the present application, the step S110 specifically comprises the following steps. Figure 2 , which shows a flowchart of a second pipeline leak detection method based on radar remote sensing provided by an embodiment of the present application. In this feasible manner, the step S110 specifically comprises the following steps.

[0065] In step S111, original radar images of the target pipeline in two time phases before and after are acquired based on a synthetic aperture radar.

[0066] In step S112, the original radar images are radiometrically calibrated and image-registered to obtain calibrated radar images.

[0067] In step S113, the calibrated radar images are denoised based on a filtering algorithm to obtain the first radar images.

[0068] That is, after the embodiment of the present application performs imaging by using the synthetic aperture radar, the radar image is radiometrically calibrated to eliminate the error of the synthetic aperture radar itself and the interference of the imaging angle; then, the two radar images after the radiometric calibration processing are image registered to improve the matching quality of the two radar images; subsequently, the two radar images after the image registration are filtered and de-noised to suppress the interference of the speckle noise.

[0069] Based on this, the embodiment of the present application enables the subsequent steps to complete the processing based on the radar image with higher quality, thereby improving the accuracy of the leak detection.

[0070] In addition, it can also be understood that in the embodiment of the present application, the specific filtering algorithm is set according to the actual situation, such as in a feasible way provided by the embodiment of the present application, the filtering algorithm is any one of Lee filtering algorithm, delicate Lee algorithm, Lee Sigma filtering algorithm, median filtering algorithm and Frost filtering algorithm.

[0071] Step S120, based on the dielectric and polarization characteristics of different water sources, the first radar image is detected for leak detection to obtain an initial detection result.

[0072] It can be understood that the common types of water sources include spring, artesian water, well water, rain water, iceberg water and glacier water. In the embodiment of the present application, since the research target is the water source in the pipeline, the types of water sources in the embodiment of the present application include tap water, rain water, domestic wastewater and industrial wastewater.

[0073] Further, because the substances contained in different types of water sources, such as salt, are different, the dielectric characteristics of different types of water sources are different, and therefore, different types of water sources correspond to their unique dielectric characteristics. Similarly, the polarization characteristics of different water sources are also related to the substances contained therein, and therefore, different types of water sources also correspond to their unique polarization characteristics.

[0074] Therefore, in the case of no leakage, the polarization characteristics and the dielectric characteristics of different water sources should remain stable. When leakage occurs, the polarization characteristics and / or the dielectric characteristics may change due to the pollution of other substances under the ground to the water source, or the water content in the pipeline decreases due to the leakage, and then the substances contained in the water body, such as salt, change and cause the polarization characteristics and / or the dielectric characteristics to change.

[0075] Based on this situation, the embodiment of the present application carries out relevant experimental verification in advance, and the radar remote sensing dielectric properties and polarization properties of different water sources are researched correspondingly, and then the radar remote sensing dielectric properties and polarization properties of different water sources under the ground are determined. Therefore, the embodiment of the present application carries out dielectric property and polarization property verification on the water source type corresponding to the radar image based on the water source type and its dielectric property and the water source type and its polarization property, so as to complete the leak detection of the pipeline.

[0076] In addition, it should be noted that the initial detection result in the embodiment of the present application refers to the pipeline in which the leak exists in the target pipeline, and the target pipeline may have multiple pipelines leaking. Therefore, the initial detection result includes one and more than one pipeline.

[0077] Step S130, based on the differential interference measurement technology, deformation analysis is carried out on the first radar image of the two time phases, and the deformation detection result is obtained.

[0078] That is, the embodiment of the present application carries out deformation detection on the radar images of the previous and subsequent time phases based on the differential interference measurement technology (DInSAR, Differential Interferometry For Synthetic Aperture Radar) to determine whether the detection target has shape change. It should be noted that the deformation detection result obtained here refers to the change of the water body.

[0079] Step S140, based on the fitting relationship between the deformation detection result and the water content, the change information corresponding to the first radar image of the two time phases is determined.

[0080] It should be understood that how to obtain the fitting relationship between the deformation detection result and the water content is a content that can be set according to actual conditions. In one possible way, the aforementioned fitting relationship is obtained through the content disclosed in the prior art.

[0081] In another possible way provided by the embodiment of the present application, the aforementioned fitting relationship is obtained by sample inversion, that is, the relationship between the water content and the deformation detection result sample is fitted by using a plurality of deformation detection result samples and the actual water content corresponding to each deformation detection result sample, so as to determine the mapping relationship / fitting relationship between different deformation detection result samples and the actual water content.

[0082] Therefore, after obtaining the deformation detection result by using the differential interference measurement technology, that is, obtaining the change of the water body, the embodiment of the present application determines the change information corresponding to the deformation detection result according to the change of the water body and the aforementioned mapping relationship / fitting relationship, that is, determines the water body change amount corresponding to the deformation detection result.

[0083] Optionally, in an implementation provided by the present application, the change information is a change range / area and a change depth of the water content.

[0084] At step S150, the initial detection result is screened based on the change information to obtain a screened detection result.

[0085] It should be understood that, in the leak detection process based on the radar remote sensing dielectric and polarization characteristics, the radar remote sensing dielectric and polarization characteristics may be affected by similar scattering characteristics of non-leak objects, that is, the initial detection result is not accurate.

[0086] Therefore, the present application embodiment will screen the initial detection result based on the change information, that is, the water body change amount, to determine whether the water body change amount in the pipeline corresponding to the plurality of leaks exceeds the preset threshold value. If so, it is determined that the initial detection result is highly probable to be true, that is, the pipeline corresponding to the initial detection result is highly probable to have a water leakage condition.

[0087] In addition, it should be noted that, although step S150 is used to screen the initial detection result output by step S120 in the present application embodiment, in an implementation, the radar image can be detected using the change information to obtain a corresponding detection result, and then the initial detection result output by step S120 and the detection result are processed in a union set to obtain the screened detection result in the present application embodiment.

[0088] At step S160, the screened detection result is input into a pre-trained network model to obtain a leak detection result of the target pipeline, wherein the network model is obtained by pre-acquiring a plurality of screened detection result samples and performing model training using the plurality of screened detection result samples.

[0089] That is, the present application embodiment further pre-acquires a plurality of screened detection results and an actual detection result corresponding to each screened detection result as samples, and performs model training using the samples, thereby obtaining the network model, to further improve the leak detection accuracy of the pipeline.

[0090] Therefore, after obtaining the screened detection result, the present application embodiment inputs the screened detection result into the network model to enable the network model to further identify / screen the screened detection result, thereby obtaining a leak detection result closest to the truth.

[0091] Based on this, the embodiment of the present application carries out multi-dimensional leak detection on the pipeline through the water source type, the dielectric property of radar remote sensing, the polarization property and the corresponding water content change of phase information, thereby reducing the false detection probability due to the use of single-dimensional information; and the embodiment of the present application also carries out secondary screening / detection based on the network model, thereby further improving the accuracy of the leak detection result.

[0092] Optionally, in one feasible manner provided by the embodiment of the present application, specifically refer to Figure 3 , a flowchart of a second radar remote sensing-based pipeline leak detection method provided by the embodiment of the present application is shown, in this feasible manner, the foregoing step S120 specifically includes:

[0093] Step S121, based on the dielectric property of radar remote sensing of different water sources, carrying out leak detection on the first radar image to obtain a first detection result;

[0094] Step S122, based on the polarization property of different water sources, carrying out leak detection on the first radar image to obtain a second detection result;

[0095] Step S123, based on the intersection of the first detection result and the second detection result, obtaining an initial detection result.

[0096] That is, the embodiment of the present application first carries out detection on the water in the pipeline appearing in the first radar image based on the prior knowledge of different types of water sources and the dielectric property of radar remote sensing thereof, and then judges whether the type of water and the dielectric property of radar remote sensing of water match the foregoing prior knowledge, if not, it indicates that there may be a leakage phenomenon, and thus it is taken as the first detection result. It should be noted that the first detection result is at least one pipeline in the target pipeline that "may have a leakage phenomenon".

[0097] It can be understood that when the target pipeline is detected, the type of water transported by the target pipeline, i.e., the water source type, is known in advance, i.e., the target pipeline transports one or more combinations of tap water, rainwater, domestic wastewater and industrial wastewater, and the prior knowledge in the embodiment of the present application is the dielectric property of radar remote sensing corresponding to tap water, the dielectric property of radar remote sensing corresponding to industrial wastewater, the dielectric property of radar remote sensing corresponding to rainwater and the dielectric property of radar remote sensing corresponding to domestic wastewater.

[0098] After obtaining the first detection result, or in the process of generating the first detection result, the embodiment of the present application further detects the water body in the pipeline appearing in the first radar image, and then determines the polarization characteristics of the water body. Then, based on the prior knowledge related to the polarization characteristics, that is, the polarization characteristics of different water sources, it is judged whether the polarization characteristics corresponding to the water body in the pipeline match the prior knowledge related to the polarization characteristics, and then the pipeline that does not match is taken as the second detection result.

[0099] Finally, the embodiment of the present application takes the intersection of the first detection result and the second detection result, thereby obtaining the leak detection result based on the polarization characteristics and the radar remote sensing dielectric characteristics, that is, the initial detection result.

[0100] In addition, it can be understood that the execution order of steps S121 and S122 is a content that can be set according to actual conditions, Figure 2 The order shown is only one of the possible ways, and steps S121 and S122 can be executed in a concurrent order, or step S121 is executed before step S122, or step S122 is executed before step S121.

[0101] Optionally, in a possible way provided by the embodiment of the present application, the fitting relationship between the deformation detection result and the water content is obtained in advance, and then the method further comprises:

[0102] Based on the synthetic aperture radar, a plurality of second radar images are obtained, wherein the plurality of second radar images correspond to the same detection target, and the plurality of second radar images are different in time phase;

[0103] The water content corresponding to each of the second radar images is determined;

[0104] Based on the differential interference measurement technology, deformation analysis is performed on each of the second radar images to obtain a deformation variable corresponding to each of the second radar images;

[0105] The water content and the deformation variable of each of the second radar images are fitted to obtain the fitting relationship.

[0106] That is, the embodiment of the present application obtains the fitting relationship between the deformation detection result and the water content based on the inversion method. Specifically, first, the synthetic aperture radar is used to image the same target multiple times to obtain a plurality of radar images different in time phase, and the plurality of radar images different in time phase are taken as samples. Then, based on the data collected in advance, the actual water content corresponding to each sample / second radar image is determined. Next, for each sample, the deformation variable corresponding to each sample is calculated based on the time phase before the time phase of the previous sample. Finally, the deformation variable and the actual water content corresponding to each sample are fitted, thereby obtaining the relationship between the actual water content and the deformation variable.

[0107] Embodiment 2

[0108] Corresponding to the pipeline leakage point detection method based on radar remote sensing provided by Embodiment 1 of the present application, Embodiment 2 of the present application further provides a pipeline leakage point detection device based on radar remote sensing, which refers to Figure 4 , shows the structure schematic diagram of the pipeline leakage point detection device based on radar remote sensing provided by the embodiment of the present application, the pipeline leakage point detection device 200 based on radar remote sensing provided by the embodiment of the present application, comprising:

[0109] The acquisition module 210 is configured to acquire first radar images of two time phases of a target pipeline based on a synthetic aperture radar.

[0110] The first detection module 220 is configured to perform leakage point detection on the first radar images based on the dielectric properties and polarization properties of radar remote sensing of different water sources to obtain an initial detection result.

[0111] The second detection module 230 is configured to perform deformation analysis on the first radar images of the two time phases based on a differential interference measurement technique to obtain a deformation detection result.

[0112] The determination module 240 is configured to determine change information corresponding to the first radar images of the two time phases based on a fitting relationship between the deformation detection result and the water content.

[0113] The screening module 250 is configured to screen the initial detection result based on the change information to obtain a screened detection result.

[0114] The result output module 260 is configured to input the screened detection result into a pre-trained network model to obtain a leakage point detection result of the target pipeline, wherein the network model is obtained by pre-acquiring a plurality of screened detection result samples and performing model training using the plurality of screened detection result samples.

[0115] Optionally, in a feasible manner provided by the embodiment of the present application, the first detection module comprises:

[0116] The leakage point detection submodule is configured to perform leakage point detection on the first radar images based on the dielectric properties of radar remote sensing of different water sources to obtain a first detection result.

[0117] The polarization detection submodule is configured to perform leakage point detection on the first radar images based on the polarization properties of different water sources to obtain a second detection result.

[0118] The result obtaining submodule is configured to obtain an initial detection result based on the intersection of the first detection result and the second detection result.

[0119] Optionally, in an implementation provided by the embodiment of the present application, the fitting relationship between the deformation detection result and the water content is obtained in advance, and the device further comprises:

[0120] an image acquisition module configured to acquire a plurality of second radar images based on the synthetic aperture radar, wherein the plurality of second radar images correspond to the same detection target, and the plurality of second radar images are different in time phase;

[0121] a water content determination module configured to determine the water content corresponding to each of the second radar images;

[0122] a deformation amount acquisition module configured to perform deformation analysis on each of the second radar images based on the differential interferometry technique to obtain a deformation amount corresponding to each of the second radar images;

[0123] a fitting module configured to fit the water content and the deformation amount of each of the second radar images to obtain the fitting relationship.

[0124] Optionally, in an implementation provided by the embodiment of the present application, the acquisition module comprises:

[0125] an original image acquisition submodule configured to acquire original radar images of two time phases before and after the target pipeline based on the synthetic aperture radar;

[0126] a calibration submodule configured to perform radiation calibration and image registration on the original radar images to obtain calibrated radar images;

[0127] a filtering submodule configured to perform noise reduction processing on the calibrated radar images based on a filtering algorithm to obtain first radar images.

[0128] Optionally, in an implementation provided by the embodiment of the present application, the filtering algorithm is any one of a Lee filtering algorithm, a refined Lee algorithm, a Lee Sigma filtering algorithm, a median filtering algorithm, and a Frost filtering algorithm.

[0129] The pipeline leakage detection device 200 based on radar remote sensing provided by the embodiment of the present application can implement each process of the pipeline leakage detection method based on radar remote sensing corresponding to the embodiment 1, and can achieve the same technical effects. To avoid repetition, details are not described here.

[0130] The embodiment of the present application further provides a computer device comprising a memory and a processor, the memory stores a computer program, and the computer program executes the pipeline leakage detection method based on radar remote sensing as described in the embodiment 1 when running on the processor.

[0131] The embodiment of the present application further provides a computer readable storage medium, and the computer readable storage medium stores a computer program.

[0132] In several embodiments provided in the present application, it should be understood that the disclosed apparatus and method can also be implemented by other manners. The apparatus embodiments described above are only schematic, for example, the flow charts and structural diagrams in the drawings show the possible implementation architectures, functions and operations of the apparatus, method and computer program product according to the embodiments of the present application. In this regard, each block in the flow charts or structural diagrams can represent a module, a program segment or a part of code, which contains one or more executable instructions for implementing the specified logic function. It should also be noted that, in alternative implementation manners, the functions noted in the blocks can also occur in different orders from those noted in the drawings. For example, two consecutive blocks can actually be executed substantially in parallel, and they can also be executed in reverse order, depending on the functions involved. It should also be noted that each block in the structural diagram and / or flow chart, and the combination of blocks in the structural diagram and / or flow chart, can be implemented by a dedicated hardware-based system for implementing the specified functions or actions, or can be implemented by a combination of dedicated hardware and computer instructions.

[0133] In addition, each functional module or unit in the embodiments of the present application can be integrated together to form an independent part, or each module can exist independently, or two or more modules can be integrated to form an independent part.

[0134] If the functions are implemented in the form of software function modules and sold or used as independent products, they can be stored in a computer readable storage medium. Based on this understanding, the technical solutions of the present application 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 for causing a computer device (which can be a smart phone, a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods described in the embodiments of the present application. The aforementioned storage medium includes: a U disk, a mobile hard disk, a read-only memory (ROM, Read-Only Memory), a random access memory (RAM, Random Access Memory), a magnetic disk or an optical disk, and various media that can store program codes.

[0135] The above merely illustrates the specific embodiments of the present application, but the protection scope of the present application is not limited thereto, any person skilled in the art can easily think of the changes or replacements within the technical range disclosed by the present application, which should be covered in the protection scope of the present application.

Claims

1. A pipeline leak detection method based on radar remote sensing, characterized in that, The method comprises the following steps: obtaining, based on synthetic aperture radar, first radar images of a target pipeline in two time phases before and after; detecting leakage points in the first radar images based on the dielectric properties and polarization properties of radar remote sensing of different water sources to obtain initial detection results; performing deformation analysis on the first radar images in the two time phases based on differential interferometric measurement technology to obtain deformation detection results; determining change information corresponding to the first radar images in the two time phases based on a fitting relationship between the deformation detection results and water content; screening the initial detection results based on the change information to obtain screened detection results; inputting the screened detection results into a pre-trained network model to obtain leakage point detection results of the target pipeline, wherein the network model is obtained by pre-acquiring a plurality of screened detection result samples and performing model training using the plurality of screened detection result samples.

2. The radar remote sensing based pipeline leak detection method of claim 1, wherein, The method of detecting leakage points in the first radar images based on the dielectric properties and polarization properties of radar remote sensing of different water sources to obtain initial detection results comprises the following steps: detecting leakage points in the first radar images based on the dielectric properties of radar remote sensing of different water sources to obtain first detection results; detecting leakage points in the first radar images based on the polarization properties of different water sources to obtain second detection results; obtaining initial detection results based on the intersection of the first detection results and the second detection results.

3. The radar remote sensing based pipeline leak detection method of claim 1, wherein, The fitting relationship between deformation detection results and water content is obtained in advance, and the method further comprises the following steps: obtaining a plurality of second radar images based on the synthetic aperture radar, wherein the plurality of second radar images correspond to the same detection target, and the plurality of second radar images are in different time phases; determining the water content corresponding to each of the second radar images; performing deformation analysis on each of the second radar images based on differential interferometric measurement technology to obtain a deformation value corresponding to each of the second radar images; fitting the water content and the deformation value of each of the second radar images to obtain the fitting relationship.

4. The radar remote sensing based pipeline leak detection method of claim 1 or 3, wherein, The method of obtaining, based on synthetic aperture radar, first radar images of a target pipeline in two time phases before and after comprises the following steps: obtaining, based on synthetic aperture radar, original radar images of the target pipeline in two time phases before and after; performing radiation calibration and image registration on the original radar images to obtain calibrated radar images; performing noise reduction processing on the calibrated radar images based on a filtering algorithm to obtain first radar images.

5. The radar remote sensing based pipeline leak detection method of claim 4, wherein, The filtering algorithm is any one of Lee filtering algorithm, refined Lee algorithm, Lee Sigma filtering algorithm, median filtering algorithm, and Frost filtering algorithm.

6. A pipeline leak detection device based on radar remote sensing, characterized in that, The method comprises the following steps: an acquisition module configured to obtain, based on synthetic aperture radar, first radar images of a target pipeline in two time phases before and after; a first detection module configured to detect leakage points in the first radar images based on the dielectric properties and polarization properties of radar remote sensing of different water sources to obtain initial detection results; a second detection module configured to perform deformation analysis on the first radar images in the two time phases based on differential interferometric measurement technology to obtain deformation detection results; The determining module is configured to determine change information corresponding to the first radar image pair of the two time phases based on a fitting relationship between the deformation detection result and the water content; The screening module is configured to screen the initial detection result based on the change information to obtain a screened detection result; The result output module is configured to input the screened detection result into a pre-trained network model to obtain a leak point detection result of the target pipeline, wherein the network model is obtained by pre-acquiring a plurality of screened detection result samples and performing model training using the plurality of screened detection result samples.

7. The radar remote sensing based pipeline leak detection apparatus as claimed in claim 6, wherein, The first detection module comprises: A leak point detection sub-module configured to perform leak point detection on the first radar image based on the dielectric properties of radar remote sensing of different water sources to obtain a first detection result; A polarization detection sub-module configured to perform leak point detection on the first radar image based on the polarization properties of different water sources to obtain a second detection result; A result obtaining sub-module configured to obtain an initial detection result based on an intersection of the first detection result and the second detection result.

8. The radar remote sensing based pipeline leak detection apparatus as claimed in claim 6, wherein, The fitting relationship between the deformation detection result and the water content is obtained by pre-acquisition, and the device further comprises: An image acquisition module configured to acquire a plurality of second radar images based on the synthetic aperture radar, wherein the plurality of second radar images correspond to the same detection target, and the plurality of second radar images are different in time phase; A water content determination module configured to determine the water content corresponding to each of the second radar images; A deformation amount acquisition module configured to perform deformation analysis on each of the second radar images based on differential interferometric measurement technology to obtain a deformation amount corresponding to each of the second radar images; A fitting module configured to fit the water content and the deformation amount of each of the second radar images to obtain the fitting relationship.

9. The radar remote sensing based pipeline leak detection apparatus as claimed in claim 6 or 8, wherein, The acquisition module comprises: An original image acquisition sub-module configured to acquire original radar images of the target pipeline in front and back two time phases based on the synthetic aperture radar; A calibration sub-module configured to perform radiation calibration and image registration on the original radar images to obtain calibrated radar images; A filtering sub-module configured to perform noise reduction processing on the calibrated radar images based on a filtering algorithm to obtain first radar images.

10. The radar remote sensing based pipeline leak detection apparatus as claimed in claim 9, wherein, The filtering algorithm is any one of Lee filtering algorithm, refined Lee algorithm, Lee Sigma filtering algorithm, median filtering algorithm, and Frost filtering algorithm.

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