Method and device for underwater three-dimensional reconstruction of inspection well based on sonar ring scan image

Abstract

The application relates to the field of electronic technology and discloses a method and device for underwater three-dimensional reconstruction of an inspection well based on a sonar ring scanning image, which comprises the following steps: based on target attitude data, reference sonar ring scanning data and target attitude data of each depth of the underwater inspection well, performing offset correction on the sonar ring scanning data of the corresponding depth to obtain target sonar ring scanning data of the corresponding depth; determining real coordinate information of a plurality of pixel points of the corresponding depth based on the target sonar ring scanning data of each depth, pixel quantity information and pixel spacing information; determining global coordinate information of the plurality of pixel points of the corresponding depth based on the target attitude data of each depth and the real coordinate information of the plurality of pixel points; and determining an underwater three-dimensional model of the inspection well based on the global coordinate information of the plurality of depths, so that the sonar technology can be adapted to the detection scene of the inspection well under high water level and turbid water, and key information such as the pipeline direction, the pipe diameter size and the structural defects in the inspection well can be clearly and accurately ascertained.

Description

Technical Field

[0001] This invention relates to the field of electronic technology, and specifically to a method and apparatus for underwater three-dimensional reconstruction of inspection wells based on sonar circumferential scanning images. Background Technology

[0002] Inspection wells, as core nodes connecting urban drainage pipelines and constructing underground drainage networks, are crucial structures for monitoring pipeline transfer status, identifying structural problems, and conducting routine maintenance. However, current drainage networks generally operate at high water levels, and the sewage inside the wells is turbid with low visibility. This renders traditional optical imaging methods such as periscopes ineffective, making it impossible to effectively image the underwater environment of the inspection well, creating a "blind spot" and causing it to lose its basic function as an important inspection node. Sonar detection technology is an important method for scanning turbid underwater environments and constructing spatial models. However, sonar scanning results are two-dimensional and cannot reflect the three-dimensional spatial structure of the inspection well. This means that current sonar products cannot be used to determine pipeline routes, diameters, and defects in the inspection well, thus limiting the further application of sonar in high-water-level inspection wells. Summary of the Invention

[0003] This invention provides a method and apparatus for underwater three-dimensional reconstruction of inspection wells based on sonar circumferential scanning images, in order to solve the problem that the sonar scanning results in related technologies are two-dimensional and difficult to reflect the three-dimensional spatial structure of the inspection well, which makes it impossible to use existing sonar products to determine the pipeline direction, pipe diameter, inspection well defects and other related information at this stage.

[0004] In a first aspect, the present invention provides a method for underwater 3D reconstruction of inspection wells based on sonar ring scan images. The method includes: acquiring sonar ring scan data at different depths underwater in the inspection well, target attitude data, reference sonar ring scan data of the inspection well, pixel count information, and pixel spacing information of the sonar ring scan data at each depth; performing offset correction on the sonar ring scan data at the corresponding depth based on the target attitude data at each depth, the reference sonar ring scan data, and the target attitude data to obtain target sonar ring scan data at the corresponding depth; determining the true coordinate information of multiple pixels at the corresponding depth based on the target sonar ring scan data at each depth, pixel count information, and pixel spacing information; determining the global coordinate information of multiple pixels at the corresponding depth based on the target attitude data at each depth and the true coordinate information of multiple pixels; and determining the underwater 3D model of the inspection well based on the global coordinate information of multiple depths.

[0005] The present invention provides an underwater 3D reconstruction method for inspection wells based on sonar circumferential scanning images. By acquiring sonar circumferential scanning data and attitude data at different depths underwater in the inspection well, and relying on reference data to complete the offset correction of sonar circumferential scanning data at each depth, it can eliminate data deviations caused by probe translation, attitude jitter, and the underwater environment, ensuring the accuracy and stability of sonar acquisition data. Then, by combining the pixel number and pixel spacing information, it completes the calculation of real coordinates, and further relies on attitude data to convert real coordinates into global coordinates. Finally, based on multi-depth global coordinates, a complete underwater 3D model of the inspection well is constructed. It can clearly and accurately identify key information such as pipeline direction, pipe diameter, and structural defects in the inspection well. This allows sonar technology to be adapted to inspection well detection scenarios in high water levels and turbid water, and restores the function of inspection wells as core detection nodes in underground drainage networks. It provides reliable digital technical support for monitoring the transfer status of drainage pipe networks, investigating structural problems, and routine maintenance, and comprehensively improves the accuracy and operation and maintenance efficiency of underwater detection of underground drainage pipe networks.

[0006] In one optional implementation, the step of performing offset correction on the sonar ring scan data at a corresponding depth based on the target attitude data, reference sonar ring scan data, and target attitude data at each depth to obtain target sonar ring scan data at the corresponding depth includes: projecting the sonar ring scan data at the corresponding depth onto the target plane based on the target attitude data at each depth to obtain first sonar ring scan data at the corresponding depth; performing Fourier transform on the first sonar ring scan data at each depth to obtain second sonar ring scan data at the corresponding depth, and performing Fourier transform on the reference sonar ring scan data to obtain target reference sonar ring scan data; calculating the cross power spectrum between the second sonar ring scan data at each depth and the target reference sonar ring scan data; determining the translation vector between the second sonar ring scan data at the corresponding depth and the target reference sonar ring scan data based on the cross power spectrum between the second sonar ring scan data at each depth and the target reference sonar ring scan data; and correcting the second sonar ring scan data based on the translation vector at each depth to obtain target sonar ring scan data at the corresponding depth.

[0007] The method provided in this optional implementation can accurately identify and correct the horizontal translation deviation during the probe's descent process through attitude projection and frequency domain cross-power spectrum calculation, effectively eliminating data errors caused by displacement and attitude disturbances. At the same time, based on the translation vector solution of frequency domain phase correlation, it has strong anti-interference ability and robustness against interference such as underwater turbidity, local occlusion, and brightness fluctuations, and can ensure the spatial consistency of sonar ring scan data at various depths, providing accurate and reliable data support for subsequent three-dimensional coordinate solution and model reconstruction.

[0008] In one optional implementation, based on sonar ring scan data and target attitude data at each depth, the sonar ring scan data at the corresponding depth is projected onto the target plane to obtain the first sonar ring scan data at the corresponding depth. This includes: performing noise reduction processing on the sonar ring scan data at each depth to obtain the noise-reduced sonar ring scan data at the corresponding depth; and projecting the noise-reduced sonar ring scan data at the corresponding depth onto the target plane based on the target attitude data at each depth to obtain the first sonar ring scan data at the corresponding depth.

[0009] The method provided in this optional implementation first performs noise reduction processing on the sonar ring scan data, which can effectively filter out transient noise such as underwater suspended particles and bubbles, and completely preserve the true structural features of the inspection well. Then, it combines the target attitude data with the projection onto the target plane, which can avoid noise interference with the attitude projection accuracy, greatly improve the purity and accuracy of the projected data, provide high-quality basic data for subsequent offset correction, coordinate calculation and 3D reconstruction, reduce calculation errors caused by noise, and ensure accurate and reliable 3D reconstruction results.

[0010] In one optional implementation, the sonar ring scan data includes multiple frames of ring scan images. Noise reduction processing is performed on the sonar ring scan data at each depth to obtain the corresponding depth-denoised sonar ring scan data. This includes: for each pixel coordinate corresponding to each depth, extracting the intensity value of that pixel coordinate in the multi-frame ring scan image data and sorting it to obtain a sorting result; using the median of the sorting results for each pixel coordinate as the final intensity value of that coordinate; and concatenating the final intensity values ​​of multiple pixel coordinates corresponding to each depth to obtain the corresponding depth-denoised sonar ring scan data.

[0011] The method provided by this optional implementation can efficiently filter out transient random noise such as underwater suspended particles and bubbles by taking the median of multiple frames per pixel for noise reduction, while completely preserving the real structural details of the manhole wall, defects, and pipe openings. This avoids the ambiguity of structural features caused by traditional filtering methods, greatly improves the purity and reliability of sonar data, and provides accurate basic data for subsequent projection, correction and 3D reconstruction.

[0012] In one optional implementation, the target pose data at each depth is determined through the following steps: acquiring the initial pose data and corresponding timestamp information at each depth; determining the first pose data within the target time period before and after the corresponding timestamp information at each depth; concatenating the first pose data and the initial pose data at each depth to obtain the second pose data; using a preset algorithm to remove extreme values ​​from the second pose data at each depth to obtain the third pose data at the corresponding depth; and extracting the median from the target pose data at each depth to obtain the denoised target pose data.

[0013] The method provided in this optional implementation method, by extracting the attitude data window through timestamps, stitching and fusing, and removing extreme values ​​and taking the median, can effectively eliminate attitude anomalies caused by probe drop jitter and sensor transient interference, greatly improve the stability and calculation accuracy of attitude data, avoid single-point attitude errors from affecting subsequent projection, correction and coordinate transformation, and provide accurate and reliable attitude data support for 3D reconstruction.

[0014] In one optional implementation, the step of determining the global coordinate information of multiple pixels at a corresponding depth based on the target pose data at each depth and the real coordinate information of multiple pixels includes: determining the rotation matrix at the corresponding depth based on the pose data at each depth; and determining the global coordinate information of multiple pixels at the corresponding depth based on the rotation matrix at each depth and the real coordinate information of multiple pixels.

[0015] The method provided in this optional implementation determines the rotation matrix through attitude data, which can accurately convert the real coordinates of pixels into globally unified coordinates, realize the absolute spatial positioning of the underwater structure of the inspection well, ensure that the data of each depth are accurately aligned in the same coordinate system, provide stable and accurate coordinate support for multi-depth data fusion and 3D model reconstruction, and ensure the real and reliable spatial position of the 3D model.

[0016] Secondly, the present invention provides an underwater 3D reconstruction device for inspection wells based on sonar ring scan images. The device includes: an acquisition module for acquiring sonar ring scan data at different depths underwater, target attitude data, reference sonar ring scan data of the inspection well, pixel count information, and pixel spacing information of the sonar ring scan data at each depth; a correction module for performing offset correction on the sonar ring scan data at corresponding depths based on the target attitude data, reference sonar ring scan data, and target attitude data at each depth to obtain target sonar ring scan data at the corresponding depth; a first determination module for determining the true coordinate information of multiple pixels at the corresponding depth based on the target sonar ring scan data at each depth, pixel count information, and pixel spacing information; a second determination module for determining the global coordinate information of multiple pixels at the corresponding depth based on the target attitude data at each depth and the true coordinate information of multiple pixels; and a third determination module for determining the underwater 3D model of the inspection well based on the global coordinate information of multiple points at each depth.

[0017] Thirdly, the present invention provides an electronic device, comprising: a memory and a processor, wherein the memory and the processor are communicatively connected to each other, the memory stores computer instructions, and the processor executes the computer instructions to perform the underwater three-dimensional reconstruction method for inspection wells based on sonar ring scan images as described in the first aspect or any corresponding embodiment.

[0018] Fourthly, the present invention provides a computer-readable storage medium storing computer instructions for causing a computer to perform the underwater three-dimensional reconstruction method for inspection wells based on sonar circumscan images as described in the first aspect or any corresponding embodiment.

[0019] Fifthly, the present invention provides a computer program product, including computer instructions for causing a computer to execute the underwater three-dimensional reconstruction method for inspection wells based on sonar circumferential scanning images as described in the first aspect or any corresponding embodiment thereof. Attached Figure Description

[0020] To more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the specific embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0021] Figure 1 This is a schematic diagram of an application scenario according to an embodiment of the present invention; Figure 2 This is a schematic diagram of the first process of a method for underwater three-dimensional reconstruction of inspection wells based on sonar ring scan images according to an embodiment of the present invention; Figure 3 This is a schematic diagram of the second process of the underwater three-dimensional reconstruction method for inspection wells based on sonar circumferential scanning images according to an embodiment of the present invention; Figure 4 This is a schematic diagram of the sonar circumferential scanning device in the embodiments of this application; Figure 5 This is a schematic diagram of the third process of the underwater three-dimensional reconstruction method for inspection wells based on sonar ring scan images according to an embodiment of the present invention; Figure 6 This is a structural block diagram of an underwater three-dimensional reconstruction device for inspection wells based on sonar circumferential scanning images according to an embodiment of the present invention; Figure 7 This is a schematic diagram of the hardware structure of an electronic device according to an embodiment of the present invention. Detailed Implementation

[0022] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0023] It is understood that before using the technical solutions disclosed in the various embodiments of the present invention, users should be informed of the types, scope of use, and usage scenarios of the personal information involved in the present invention and their authorization should be obtained in accordance with relevant laws and regulations through appropriate means.

[0024] The terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of that feature. In the description of this invention, "a plurality of" means two or more, unless otherwise explicitly specified.

[0025] As an optional application scenario of this invention, the specific application environment architecture or specific hardware architecture on which the underwater 3D reconstruction method for inspection wells based on sonar ring scan images depends is described herein. Figure 1 As shown, the architecture system may include at least one terminal device and at least one server. Figure 1 The system is illustrated in the example, which includes a computer 101, a mobile terminal 102, and a server 103, and the terminal devices such as the computer 101 and the mobile terminal 102 are connected to the server 103 through a network 110.

[0026] Specifically, the terminal device can be a smartphone, tablet, laptop, PDA, desktop computer, game console, smart TV, smart wearable device, in-vehicle terminal, VR (Virtual Reality) device, AR (Augmented Reality) device, etc. Server 103 can be a standalone physical server, a server cluster, a distributed system, or a cloud server providing cloud services. Network 110 can be a wired or wireless network, examples of which include, but are not limited to, the Internet, corporate intranet, local area network, wide area network, mobile communication network, and combinations thereof.

[0027] In view of this, this application provides a method for underwater 3D reconstruction of inspection wells based on sonar circumferential scanning images. This method can be applied to a single server to achieve underwater 3D reconstruction of inspection wells. The method provided in this application acquires sonar circumferential scanning data and attitude data at different depths underwater in the inspection well. It then uses reference data to correct the offset of the sonar circumferential scanning data at each depth, eliminating data deviations caused by probe translation, attitude jitter, and the underwater environment. This ensures the accuracy and stability of the sonar-acquired data. Furthermore, it combines pixel count and pixel spacing information to calculate the true coordinates. Finally, it uses attitude data to convert the true coordinates into global coordinates, ultimately constructing a complete underwater 3D model of the inspection well based on multi-depth global coordinates. This model can clearly and accurately identify key information such as the pipe routing, pipe diameter, and structural defects within the inspection well. It allows sonar technology to be adapted to inspection well detection scenarios in high-water levels and turbid water, restoring the function of inspection wells as core detection nodes in underground drainage networks. This provides reliable digital technical support for monitoring the transfer status of drainage pipe networks, investigating structural problems, and routine maintenance, comprehensively improving the accuracy and operational efficiency of underwater inspection of underground drainage pipe networks.

[0028] According to an embodiment of the present invention, an embodiment of an underwater three-dimensional reconstruction method for inspection wells based on sonar ring scan images is provided. It should be noted that the steps shown in the flowchart in the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions. Furthermore, although a logical order is shown in the flowchart, in some cases, the steps shown or described may be executed in a different order than that shown here.

[0029] This embodiment provides a method for underwater 3D reconstruction of inspection wells based on sonar ring scan images, which can be used in the aforementioned server. Figure 2 This is a flowchart of an underwater three-dimensional reconstruction method for inspection wells based on sonar ring scan images according to an embodiment of the present invention, as follows: Figure 2 As shown, the process includes the following steps: Step S201: Obtain sonar ring scan data at different underwater depths of the inspection well, target attitude data, reference sonar ring scan data of the inspection well, pixel count information and pixel spacing information of sonar ring scan data at each depth.

[0030] For example, the sonar circumferential scan data at different depths underwater in the inspection well consists of raw two-dimensional sonar image data acquired by lowering the circumferential scan sonar probe to different depths underwater in the inspection well. Target attitude data is the azimuth angle, roll angle, and pitch angle data corresponding to each depth probe, acquired by an attitude sensor. The reference sonar circumferential scan data is the sonar circumferential scan image acquired when the probe has just entered the water. The pixel count information for each depth's sonar circumferential scan data includes the width and height pixel values ​​of the sonar circumferential scan image. Pixel spacing information includes the actual physical distance corresponding to a single pixel in the sonar image, including lateral and longitudinal spacing.

[0031] Step S202: Based on the target attitude data, reference sonar ring scan data and target attitude data at each depth, offset correction is performed on the sonar ring scan data at the corresponding depth to obtain the target sonar ring scan data at the corresponding depth.

[0032] For example, in the embodiments of this application, the sonar ring scan data at the corresponding depth can be projected onto the reference plane based on the target attitude data at each depth. Then, the cross power spectrum between the projected data and the reference sonar ring scan data is calculated by Fourier transform. Based on this, the translation vector between the two is calculated. Finally, the sonar ring scan data is corrected using the translation vector to eliminate the positional offset caused by the probe translation and obtain accurate target sonar ring scan data.

[0033] Step S203: Determine the true coordinate information of multiple pixels at the corresponding depth based on the target sonar ring scan data, pixel quantity information and pixel spacing information at each depth.

[0034] For example, in this embodiment of the application, the actual coordinate information can be determined by the following formula:

[0035]

[0036] in, Indicates the width in pixels. Indicates the height in pixels. This represents the actual physical distance corresponding to a single pixel in the horizontal (x-direction) of the image. This represents the actual physical distance corresponding to a single pixel in the vertical (y-direction) of the image; This represents the x-coordinate of a single pixel in a sonar swathe image. This represents the original image pixel ordinate of a single pixel in a sonar circular scan image. , This represents the actual physical coordinates of the pixel in the local scanning plane of the probe after the conversion, and i represents the traversal index of the pixel.

[0037] Step S204: Determine the global coordinate information of multiple pixels at the corresponding depth based on the target pose data at each depth and the real coordinate information of multiple pixels.

[0038] For example, in this embodiment of the application, a three-dimensional spatial rotation matrix is ​​first generated based on the target pitch, roll, and yaw attitude angle parameters at each depth; then, the local true coordinates of each pixel, obtained by converting the pixel spacing in the previous step and with the probe as the origin, are substituted into the corresponding rotation matrix to complete the spatial attitude rotation transformation and correct the coordinate deviation caused by the probe attitude offset; finally, combined with the underwater vertical elevation position corresponding to each depth, a full spatial coordinate system mapping is completed, and the planar coordinates under the probe local coordinate system are transformed to the unified global world coordinate system of the inspection well, and finally the global coordinate information of all pixels is output.

[0039] Step S205: Determine the underwater three-dimensional model of the inspection well based on global coordinate information at multiple depths.

[0040] For example, in this embodiment of the application, the global three-dimensional coordinates of all pixels calculated at each depth layer are summarized in the whole domain to form a discrete point cloud set covering the entire underwater space of the inspection well. Based on the spatial position correlation of the data at each depth, data fusion and spatial surface reconstruction are completed to accurately fit the complete spatial morphology of the inspection well wall outline, the direction and size of the connecting pipes, and the internal structural defects, thereby generating a three-dimensional model that can completely represent the real underwater structure of the inspection well.

[0041] The underwater 3D reconstruction method for inspection wells based on sonar circumferential scanning images provided in this embodiment acquires sonar circumferential scanning data and attitude data at different depths underwater in the inspection well. It then uses reference data to correct the offset of the sonar circumferential scanning data at each depth, eliminating data deviations caused by probe translation, attitude jitter, and the underwater environment. This ensures the accuracy and stability of the sonar-acquired data. Furthermore, it combines pixel count and pixel spacing information to calculate the true coordinates, and uses attitude data to convert the true coordinates into global coordinates. Finally, based on multi-depth global coordinates, a complete underwater 3D model of the inspection well is constructed. This model can clearly and accurately identify key information such as the pipe routing, pipe diameter, and structural defects within the inspection well. It allows sonar technology to be adapted to inspection well detection scenarios in high-water levels and turbid water, restoring the function of the inspection well as a core detection node in the underground drainage network. This provides reliable digital technical support for monitoring the transfer status of drainage pipe networks, investigating structural problems, and routine maintenance, comprehensively improving the accuracy and operational efficiency of underwater inspection of underground drainage pipe networks.

[0042] This embodiment provides a method for underwater 3D reconstruction of inspection wells based on sonar ring scan images, which can be used in the aforementioned server. Figure 3 This is a flowchart of an underwater three-dimensional reconstruction method for inspection wells based on sonar ring scan images according to an embodiment of the present invention, as follows: Figure 3 As shown, the process includes the following steps: Step S301: Acquire sonar ring scan data at different underwater depths of the inspection well, target attitude data, reference sonar ring scan data of the inspection well, pixel count information, and pixel spacing information for the sonar ring scan data at each depth. For details, please refer to [link to relevant documentation]. Figure 2 Step S201 of the illustrated embodiment will not be described again here.

[0043] Specifically, the target pose data at each depth is determined through the following steps: Step a1: Obtain the initial pose data and corresponding timestamp information for each depth.

[0044] For example, in the embodiments of this application, during the data acquisition stage at various depths underwater in the inspection well, the original initial three-axis attitude data output in real time by the attitude sensor is acquired simultaneously, and the precise acquisition time information corresponding to each set of initial attitude data is retained.

[0045] Step a2: Determine the first pose data of the target time period before and after the timestamp information corresponding to each depth.

[0046] For example, in this embodiment of the application, the pitch angle within the time interval dt before and after the current image timestamp is extracted. Roll angle and azimuth .

[0047] Step a3: The first pose data at each depth and the initial pose data are stitched together to obtain the second pose data.

[0048] For example, the original initial attitude data corresponding to each depth is sequentially spliced ​​and integrated with the first attitude data obtained from the aforementioned time interval to form a complete and continuous attitude data sequence, thereby obtaining the second attitude data for the corresponding depth.

[0049] Step a4: Use a preset algorithm to remove extreme values ​​from the second pose data at each depth to obtain the third pose data at the corresponding depth.

[0050] For example, a pre-defined outlier removal algorithm is used to perform a full-domain traversal detection on the second attitude data sequence after time-series stitching at each depth. This identifies and removes extreme outlier data caused by underwater disturbances and instantaneous sensor errors, eliminating interference from distorted bad values ​​and retaining continuous, stable, and valid attitude information. This yields the processed third attitude data for the corresponding depth, providing clean and reliable data samples for subsequent median noise reduction optimization of attitude data. The outlier removal algorithm may include, but is not limited to, the Interquartile Range (IQR) algorithm.

[0051] Step a5: Extract the median of the target pose data at each depth to obtain the denoised target pose data.

[0052] For example, in this embodiment of the application, the median of each angle in the target attitude data at each depth is recorded as the pitch angle corresponding to the current sonar influence. Roll angle and azimuth .

[0053] Step S302: Based on the target attitude data, reference sonar ring scan data and target attitude data at each depth, offset correction is performed on the sonar ring scan data at the corresponding depth to obtain the target sonar ring scan data at the corresponding depth.

[0054] Specifically, step S302 includes: Step S3021: Based on the target attitude data at each depth, project the sonar ring scan data at the corresponding depth onto the target plane to obtain the first sonar ring scan data at the corresponding depth.

[0055] In some optional implementations, step S3021 above includes: Step b1: Denoise the sonar ring scan data at each depth to obtain the denoised sonar ring scan data at the corresponding depth.

[0056] In some optional implementations, the sonar swathe data includes multiple frames of swathe images acquired by a sonar swathe device, the structure of which is shown in the schematic diagram below. Figure 4 As shown, the system includes a telescopic rod 1, a ring-scan sonar probe 2, an attitude sensor 3, a depth sensor 4 (for recording water depth), a first platform 5, a level gauge 6, and a second platform 7. The attitude sensor 3 records the orientation angle (along the Z-axis), roll angle (along the Y-axis), and pitch angle (along the X-axis). The bottom of the depth gauge should extend beyond the ring-scan sonar probe, and the distance between the bottom of the depth gauge and the ring-scan sonar probe is h. a The sonar is aligned with the positive Y-axis of the attitude sensor. Specific data acquisition steps include: (1) Use RTK to record the center coordinates (X0, Y0) and elevation Hs of the inspection well. Set up a second platform 7 at the wellhead and use a level gauge to record the distance D from the well surface to the liquid surface. w The water surface elevation H is obtained. w = H s – D w .

[0057] (2) Place the telescopic rod with the first platform 5 inspection well in the water and turn on the ring scan sonar probe, attitude and water pressure sensor.

[0058] (3) When the platform just enters the water, store the sonar circumferential scan image and record it as P0. At this time, according to the data of the attitude sensor, the pitch angle and attitude angle should be 0 as much as possible, and the center of the sonar head should be in the center of the inspection well, and the direction angle should be pointing due north.

[0059] (4) Hold the telescopic pole and gradually lower the platform. Record the sonar circumferential scan image as Pi every 10cm. At the same time, record the accurate water depth h using a water pressure gauge. i Corresponding elevation H i = H w – h i - h a Pitch angle recorded by attitude sensor Roll angle and azimuth During recording, data from multiple sensors are fused, and real-time sonar scanning images are observed during the descent. If a pipe opening or damaged area is found, encrypted slices can be prepared.

[0060] Step a1 above includes: Step b11: For each pixel coordinate corresponding to each depth, extract the intensity value of that pixel coordinate in the multi-frame circular scan image data and sort it to obtain the sorting result.

[0061] For example, in this embodiment of the application, all pixel coordinates of the sonar ring scan images at each depth are traversed. For each fixed pixel position, the echo intensity value corresponding to it in all multi-frame ring scan images acquired at the same depth is completely retrieved. Then, all intensity data corresponding to a single pixel are arranged in order of numerical value to form an intensity value sorting structure exclusive to each pixel.

[0062] Step b12: The median of the sorted results corresponding to each pixel coordinate is used as the final intensity value of that coordinate.

[0063] For example, in this embodiment of the application, for the sorted sequence of all intensity values ​​corresponding to each pixel coordinate, the median value of the middle position of the sequence is selected and determined as the final echo intensity of the pixel, thereby eliminating underwater random noise interference and retaining the real structure signal.

[0064] Step b13: The final intensity values ​​of multiple pixel coordinates corresponding to each depth are stitched together to obtain the sonar ring scan data after noise reduction at the corresponding depth.

[0065] For example, in this embodiment of the application, the final intensity values ​​corresponding to all pixels are sequentially integrated and stitched together according to the original spatial arrangement order of each pixel coordinate in the image, and a complete sonar ring scan image is reconstructed, thereby obtaining the sonar ring scan data after corresponding depth denoising.

[0066] Step b2: Based on the target attitude data at each depth, project the noise-reduced sonar ring scan data at the corresponding depth onto the target plane to obtain the first sonar ring scan data at the corresponding depth.

[0067] For example, the target plane may include, but is not limited to, the XY plane. In this embodiment of the application, the sonar image Pi is calculated according to the elevation angle. Roll angle and azimuth Projecting this onto the xy plane yields the first sonar ring scan data, as shown in the following formula:

[0068]

[0069] in, This represents the elevation angle of the sonar probe at the acquisition time corresponding to the i-th pixel; This represents the roll angle of the sonar probe at the time of acquisition corresponding to the i-th pixel. This represents the azimuth angle of the sonar probe at the time of acquisition corresponding to the i-th pixel; This represents the physical X-axis coordinate of the i-th pixel after it has undergone a three-axis attitude rotation transformation and been projected onto the unified XY reference target plane, which is the abscissa of the first sonar ring scan data. The vertical axis represents the first sonar ring scan data. , This represents the physical coordinates of the i-th pixel within the local scan plane of the sonar probe.

[0070] Step S3022: Perform Fourier transform on the first sonar ring scan data corresponding to each depth to obtain the second sonar ring scan data corresponding to the depth; perform Fourier transform on the reference sonar ring scan data to obtain the target reference sonar ring scan data.

[0071] For example, in the embodiments of this application, the target reference sonar ring scan data can be represented by the following formula:

[0072] in, This represents the target baseline sonar ring scan data. This represents the baseline sonar circumferential scan data. The horizontal and vertical coordinates (frequency independent variables) in the two-dimensional frequency domain correspond to the frequency components of the spatial image in the horizontal and vertical directions. They are the exclusive coordinates of the frequency domain space after the Fourier transform, and are distinct from the spatial domain coordinates. One-to-one correspondence.

[0073] The second sonar circumferential scan data can be expressed by the following formula:

[0074] in, This indicates the second sonar scan data. This represents the baseline sonar circumferential scan data. The horizontal and vertical coordinates (frequency independent variables) in the two-dimensional frequency domain correspond to the frequency components of the spatial image in the horizontal and vertical directions. They are the exclusive coordinates of the frequency domain space after the Fourier transform, and are distinct from the spatial domain coordinates. One-to-one correspondence.

[0075] Step S3023: Calculate the cross power spectrum between the second sonar ring scan data at each depth and the target reference sonar ring scan data.

[0076] For example, in this embodiment of the application, based on the Fourier translation theorem, the second sonar ring scan data can be expressed by the following formula:

[0077] in, This indicates that the original reference image has undergone a complete change. The resulting spatial domain image after spatial translation Represents the imaginary unit. Represents the pure phase factor of spatial translation. This represents the global translation offset of the image to be corrected relative to the reference image; the meanings of the other variables will not be elaborated further.

[0078] Will Multiply complex conjugate Then, normalization (dividing by its own amplitude) is performed to define the cross-power spectrum. :

[0079] in, This represents the cross power spectrum; the meanings of the other variables will not be elaborated further.

[0080] Substitution The expression:

[0081] The meanings of each variable will not be elaborated further.

[0082] because ,and Therefore, the above formula simplifies to:

[0083] in, This represents the pure phase factor for spatial translation; the meanings of the other variables will not be elaborated further.

[0084] Step S3024: Based on the cross power spectrum between the second sonar ring scan data at each depth and the target reference sonar ring scan data, determine the translation vector between the second sonar ring scan data at the corresponding depth and the target reference sonar ring scan data.

[0085] For example, in the embodiments of this application, the cross-power spectrum is taken. Inverse Fourier Transform :

[0086] in, This represents the pure phase factor for spatial translation; the meanings of the other variables will not be elaborated further.

[0087] The inverse Fourier transform of a pure complex exponential function is a Dirac delta function. There is a sharp peak at that point:

[0088] After performing phase correlation on two images that differ only in translation, the result is... The coordinates of the brightest points on the image are the translation vectors between them. .

[0089] Step S3025: Correct the second sonar ring scan data based on the translation vectors of each depth to obtain the target sonar ring scan data at the corresponding depth.

[0090] For example, in this embodiment of the application, all contour pixels in the image are traversed, and translation compensation correction is performed on the planar coordinates of each point after three-axis attitude projection. The inter-layer position misalignment caused by the horizontal swing drift during the descent of the downhole probe is offset by coordinate difference calculation, the spatial coordinate deviation of all pixels is corrected, and the accurate planar coordinates after correction are output. , ). For the corrected sonar ring scan data ( , According to pitch angle Roll angle and azimuth The data was restored to obtain the target sonar ring scan data:

[0091]

[0092]

[0093] in, , This represents the pixel coordinates in the target sonar ring scan data.

[0094] Step S303: Based on the target sonar ring scan data at each depth, pixel count information, and pixel spacing information, determine the true coordinate information of multiple pixels at the corresponding depth. For details, please refer to [link to relevant documentation]. Figure 2 Step S203 of the illustrated embodiment will not be described again here.

[0095] Step S304: Based on the target pose data at each depth and the real coordinate information of multiple pixels, determine the global coordinate information of multiple pixels at the corresponding depth. For details, please refer to [link to relevant documentation]. Figure 2 Step S203 of the illustrated embodiment will not be described again here.

[0096] Step S305: Determine the underwater 3D model of the inspection well based on global coordinate information from multiple depths. For details, please refer to [link to relevant documentation]. Figure 2 Step S205 of the illustrated embodiment will not be described again here.

[0097] This embodiment provides a method for underwater 3D reconstruction of inspection wells based on sonar ring scan images, which can be used in the aforementioned server. Figure 5 This is a flowchart of an underwater three-dimensional reconstruction method for inspection wells based on sonar ring scan images according to an embodiment of the present invention, as follows: Figure 5 As shown, the process includes the following steps: Step S501: Acquire sonar ring scan data at different underwater depths of the inspection well, target attitude data, reference sonar ring scan data of the inspection well, pixel count information, and pixel spacing information for the sonar ring scan data at each depth. For details, please refer to [link to relevant documentation]. Figure 3 Step S301 of the illustrated embodiment will not be described again here.

[0098] Step S502: Based on the target attitude data at each depth, the reference sonar circular scan data, and the target attitude data, offset correction is performed on the sonar circular scan data at the corresponding depth to obtain the target sonar circular scan data at the corresponding depth. For details, please refer to [link to relevant documentation]. Figure 3 Step S302 of the illustrated embodiment will not be described again here.

[0099] Step S503: Based on the target sonar ring scan data at each depth, pixel count information, and pixel spacing information, determine the true coordinate information of multiple pixels at the corresponding depth. For details, please refer to [link to relevant documentation]. Figure 3 Step S303 of the illustrated embodiment will not be described again here.

[0100] Step S504: Based on the target pose data at each depth and the real coordinate information of multiple pixels, determine the global coordinate information of multiple pixels at the corresponding depth. For details, please refer to [link to relevant documentation]. Figure 3 Step S304 of the illustrated embodiment will not be described again here.

[0101] Specifically, step S504 includes: Step S5041: Determine the rotation matrix for the corresponding depth based on the target pose data at each depth.

[0102] For example, in an embodiment of this application, the rotation matrix can be represented by the following formula:

[0103]

[0104]

[0105]

[0106]

[0107]

[0108]

[0109]

[0110]

[0111] The meanings of each variable will not be elaborated further.

[0112] Step S5042: Determine the global coordinate information of multiple pixels at the corresponding depth based on the rotation matrix of each depth and the real coordinate information of multiple pixels.

[0113] For example, in this embodiment of the application, the global coordinate information can be determined by the following formula:

[0114]

[0115]

[0116] Here, X, Y, and Z represent global coordinates, and the meanings of the other variables will not be elaborated further.

[0117] Step S505: Determine the underwater 3D model of the inspection well based on global coordinate information from multiple depths. For details, please refer to [link to relevant documentation]. Figure 3 Step S305 of the illustrated embodiment will not be described again here.

[0118] This embodiment also provides an underwater 3D reconstruction device for inspection wells based on sonar circumferential scanning images. This device is used to implement the above embodiments and preferred embodiments, and details already described will not be repeated. As used below, the term "module" can refer to a combination of software and / or hardware that performs a predetermined function. Although the device described in the following embodiments is preferably implemented in software, hardware implementation, or a combination of software and hardware, is also possible and contemplated.

[0119] This embodiment provides an underwater 3D reconstruction device for inspection wells based on sonar circumferential scanning images, such as... Figure 6 As shown, it includes: The acquisition module 601 is used to acquire sonar ring scan data at different underwater depths of the inspection well, target attitude data, reference sonar ring scan data of the inspection well, pixel quantity information and pixel spacing information of sonar ring scan data at each depth; The correction module 602 is used to perform offset correction on the sonar ring scan data at the corresponding depth based on the target attitude data, the reference sonar ring scan data and the target attitude data at each depth, so as to obtain the target sonar ring scan data at the corresponding depth. The first determining module 603 is used to determine the real coordinate information of multiple pixels at a corresponding depth based on the target sonar ring scan data, pixel quantity information and pixel spacing information at each depth. The second determining module 604 is used to determine the global coordinate information of multiple pixels at the corresponding depth based on the target pose data at each depth and the real coordinate information of multiple pixels. The third determining module 605 is used to determine the underwater three-dimensional model of the inspection well based on the global coordinate information of multiple points at each depth.

[0120] In some alternative implementations, the correction module 602 includes: The projection submodule is used to project the sonar ring scan data at each depth onto the target plane based on the target attitude data at each depth, so as to obtain the first sonar ring scan data at the corresponding depth. The transformation submodule is used to perform Fourier transform on the first sonar ring scan data corresponding to each depth to obtain the second sonar ring scan data corresponding to the depth, and to perform Fourier transform on the reference sonar ring scan data to obtain the target reference sonar ring scan data. The calculation submodule is used to calculate the cross power spectrum between the second sonar ring scan data and the target reference sonar ring scan data at each depth. The first determining submodule is used to determine the translation vector between the second sonar ring scan data and the target reference sonar ring scan data at the corresponding depth based on the cross power spectrum between the second sonar ring scan data and the target reference sonar ring scan data at each depth. The correction submodule is used to correct the second sonar ring scan data based on the translation vectors at each depth to obtain the target sonar ring scan data at the corresponding depth.

[0121] In some alternative implementations, the projection submodule includes: The processing unit is used to perform noise reduction processing on the sonar ring scan data at each depth to obtain the noise-reduced sonar ring scan data at the corresponding depth. The projection unit is used to project the noise-reduced sonar ring scan data at each depth onto the target plane based on the target attitude data at each depth, so as to obtain the first sonar ring scan data at the corresponding depth.

[0122] In some optional implementations, the processing unit includes: The extraction sub-unit is used to extract the intensity value of each pixel coordinate in the multi-frame circular scan image data for each depth and sort it to obtain the sorting result. Determine the sub-unit, which is used to take the median of the sorted results corresponding to each pixel coordinate as the final intensity value of that coordinate; The stitching sub-unit is used to stitch together the final intensity values ​​of multiple pixel coordinates corresponding to each depth to obtain the sonar ring scan data after noise reduction at the corresponding depth.

[0123] In some alternative implementations, the target pose data at each depth is determined through the following steps: Obtain the initial pose data and corresponding timestamp information for each depth; Determine the first pose data of the target time period before and after the timestamp information corresponding to each depth; The first pose data at each depth and the initial pose data are concatenated to obtain the second pose data; The extreme values ​​in the second pose data at each depth are removed using a preset algorithm to obtain the third pose data at the corresponding depth. The median of the target pose data at each depth is extracted to obtain the denoised target pose data.

[0124] In some alternative implementations, the second determining module 604 includes: The second determination submodule is used to determine the rotation matrix for the corresponding depth based on the pose data at each depth. The third determination submodule is used to determine the global coordinate information of multiple pixels at the corresponding depth based on the rotation matrix of each depth and the real coordinate information of multiple pixels.

[0125] The underwater 3D reconstruction device for inspection wells based on sonar circumferential scanning images provided in this invention can execute the underwater 3D reconstruction method for inspection wells based on sonar circumferential scanning images provided in any embodiment of this invention, and has the corresponding functional modules and beneficial effects for executing the method. Further functional descriptions of the above modules and units are the same as in the corresponding embodiments described above, and will not be repeated here.

[0126] Figure 7 This is a schematic diagram of the structure of an electronic device provided in an embodiment of the present invention.

[0127] The following is a detailed reference. Figure 7 This diagram illustrates a suitable structural schematic for implementing an electronic device according to embodiments of the present invention. The electronic device may include a processor (e.g., a central processing unit, graphics processor, etc.) 701, which can perform various appropriate actions and processes based on a program stored in read-only memory (ROM) 702 or a program loaded from memory 708 into random access memory (RAM) 703. The RAM 703 also stores various programs and data required for the operation of the electronic device. The processor 701, ROM 702, and RAM 703 are interconnected via a bus 704. An input / output (I / O) interface 705 is also connected to the bus 704.

[0128] Typically, the following devices can be connected to I / O interface 705: input devices 706 including, for example, touchscreens, touchpads, keyboards, mice, cameras, microphones, accelerometers, gyroscopes, etc.; output devices 707 including, for example, liquid crystal displays (LCDs), speakers, vibrators, etc.; memory devices 708 including, for example, magnetic tapes, hard disks, etc.; and communication devices 709. Communication device 709 allows electronic devices to exchange data via wireless or wired communication with other devices. Although Figure 7 Electronic devices with various devices are shown, but it should be understood that it is not required to implement or have all of the devices shown, and more or fewer devices may be implemented or have instead.

[0129] In particular, according to embodiments of the present invention, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, embodiments of the present invention include a computer program product comprising a computer program carried on a non-transitory computer-readable medium, the computer program containing program code for performing the methods shown in the flowcharts. In such embodiments, the computer program can be downloaded and installed from a network via a communication device 709, or installed from a memory 708, or installed from a ROM 702. When the computer program is executed by the processor 701, it performs the functions defined in the underwater three-dimensional reconstruction method for inspection wells based on sonar ring scan images according to embodiments of the present invention.

[0130] Figure 7 The electronic device shown is merely an example and should not be construed as limiting the functionality and scope of use of the embodiments of the present invention.

[0131] This invention also provides a computer-readable storage medium. The methods described above according to embodiments of the invention can be implemented in hardware or firmware, or implemented as computer code that can be recorded on a storage medium, or implemented as computer code downloaded via a network and originally stored on a remote storage medium or a non-transitory machine-readable storage medium and then stored on a local storage medium. Thus, the methods described herein can be processed by software stored on a storage medium using a general-purpose computer, a dedicated processor, or programmable or dedicated hardware. The storage medium can be a magnetic disk, optical disk, read-only memory, random access memory, flash memory, hard disk, or solid-state drive, etc.; further, the storage medium can also include combinations of the above types of memory. It is understood that computers, processors, microprocessor controllers, or programmable hardware include storage components capable of storing or receiving software or computer code. When the software or computer code is accessed and executed by the computer, processor, or hardware, the underwater three-dimensional reconstruction method for inspection wells based on sonar ring scan images shown in the above embodiments is implemented.

[0132] A portion of this invention can be applied as a computer program product, such as computer program instructions, which, when executed by a computer, can invoke or provide the methods and / or technical solutions according to the invention through the operation of the computer. Those skilled in the art will understand that the forms in which computer program instructions exist in a computer-readable medium include, but are not limited to, source files, executable files, installation package files, etc. Correspondingly, the ways in which computer program instructions are executed by a computer include, but are not limited to: the computer directly executing the instructions, or the computer compiling the instructions and then executing the corresponding compiled program, or the computer reading and executing the instructions, or the computer reading and installing the instructions and then executing the corresponding installed program. Here, the computer-readable medium can be any available computer-readable storage medium or communication medium accessible to a computer.

[0133] Although embodiments of the invention have been described in conjunction with the accompanying drawings, those skilled in the art can make various modifications and variations without departing from the spirit and scope of the invention, and such modifications and variations all fall within the scope defined by the appended claims.

Claims

1. A method for underwater three-dimensional reconstruction of inspection wells based on sonar ring scan images, characterized in that, The method includes: Acquire sonar ring scan data, target attitude data, reference sonar ring scan data of the inspection well at different underwater depths, pixel count information and pixel spacing information of sonar ring scan data at each depth; Based on the target attitude data at each depth, the reference sonar ring scan data, and the target attitude data, offset correction is performed on the sonar ring scan data at the corresponding depth to obtain the target sonar ring scan data at the corresponding depth. Based on the target sonar ring scan data, pixel quantity information and pixel spacing information at each depth, the true coordinate information of multiple pixels at the corresponding depth is determined. The global coordinate information of multiple pixels at the corresponding depth is determined based on the target pose data at each depth and the real coordinate information of multiple pixels. The underwater 3D model of the inspection well is determined based on the global coordinate information at multiple depths.

2. The method according to claim 1, characterized in that, The step of performing offset correction on the sonar circular scan data at the corresponding depth based on the target attitude data at each depth, the reference sonar circular scan data, and the target attitude data to obtain the target sonar circular scan data at the corresponding depth includes: Based on the target attitude data at each depth, the sonar ring scan data at the corresponding depth is projected onto the target plane to obtain the first sonar ring scan data at the corresponding depth. Fourier transform is performed on the first sonar loop scan data corresponding to each depth to obtain the second sonar loop scan data corresponding to the depth. Fourier transform is performed on the reference sonar loop scan data to obtain the target reference sonar loop scan data. Calculate the cross-power spectrum between the second sonar ring scan data and the target reference sonar ring scan data at each depth; Based on the cross power spectrum between the second sonar ring scan data and the target reference sonar ring scan data at each depth, the translation vector between the second sonar ring scan data and the target reference sonar ring scan data at the corresponding depth is determined. The second sonar ring scan data is corrected based on the translation vectors at each depth to obtain the target sonar ring scan data at the corresponding depth.

3. The method according to claim 2, characterized in that, The sonar ring scan data and target attitude data based on each depth are projected onto the target plane to obtain the first sonar ring scan data at the corresponding depth, including: The sonar ring scan data at each depth were denoised to obtain the denoised sonar ring scan data at the corresponding depth. Based on the target attitude data at each depth, the denoised sonar ring scan data at the corresponding depth is projected onto the target plane to obtain the first sonar ring scan data at the corresponding depth.

4. The method according to claim 3, characterized in that, The sonar ring scan data includes multiple frames of ring scan images. The noise reduction processing of the sonar ring scan data at each depth to obtain the corresponding depth-denoised sonar ring scan data includes: For each pixel coordinate corresponding to each depth, the intensity value of that pixel coordinate in the multi-frame circular scan image data is extracted and sorted to obtain the sorting result; The median of the sorted results corresponding to each pixel coordinate is used as the final intensity value for that coordinate; The final intensity values ​​corresponding to multiple pixel coordinates at each depth are stitched together to obtain the noise-reduced sonar ring scan data at the corresponding depth.

5. The method according to any one of claims 1 to 4, characterized in that, The target pose data at each depth are determined through the following steps: Obtain the initial pose data and corresponding timestamp information for each depth; Determine the first pose data of the target time period before and after the timestamp information corresponding to each depth; The first pose data at each depth and the initial pose data are concatenated to obtain the second pose data; The extreme values ​​in the second pose data at each depth are removed using a preset algorithm to obtain the third pose data at the corresponding depth. The median of the target pose data at each depth is extracted to obtain the denoised target pose data.

6. The method according to any one of claims 1 to 4, characterized in that, The step of determining the global coordinate information of multiple pixels at a corresponding depth based on the target pose data at each depth and the real coordinate information of multiple pixels includes: The rotation matrix for each depth is determined based on the pose data at each depth. The global coordinate information of multiple pixels at each depth is determined based on the rotation matrix at each depth and the actual coordinate information of multiple pixels.

7. A device for underwater three-dimensional reconstruction of inspection wells based on sonar circumferential scanning images, characterized in that, The device includes: The acquisition module is used to acquire sonar ring scan data, target attitude data, reference sonar ring scan data of the inspection well at different underwater depths, pixel count information and pixel spacing information of sonar ring scan data at each depth; The correction module is used to perform offset correction on the sonar ring scan data at the corresponding depth based on the target attitude data at each depth, the reference sonar ring scan data, and the target attitude data, so as to obtain the target sonar ring scan data at the corresponding depth. The first determining module is used to determine the real coordinate information of multiple pixels at the corresponding depth based on the target sonar ring scan data, pixel quantity information and pixel spacing information at each depth. The second determining module is used to determine the global coordinate information of multiple pixels at the corresponding depth based on the target pose data at each depth and the real coordinate information of multiple pixels. The third determination module is used to determine the underwater three-dimensional model of the inspection well based on the global coordinate information of multiple points at each depth.

8. An electronic device, characterized in that, include: The system includes a memory and a processor, which are interconnected. The memory stores computer instructions, and the processor executes the computer instructions to perform the underwater three-dimensional reconstruction method for inspection wells based on sonar ring scan images as described in any one of claims 1 to 6.

9. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer instructions for causing the computer to perform the underwater three-dimensional reconstruction method for inspection wells based on sonar circumferential scanning images as described in any one of claims 1 to 6.

10. A computer program product, characterized in that, Includes computer instructions for causing a computer to execute the underwater three-dimensional reconstruction method for inspection wells based on sonar circumferential scanning images as described in any one of claims 1 to 6.

Images