A method, device and medium for monitoring siltation based on sonar point cloud

Abstract

The present invention discloses a method, device and medium for monitoring siltation based on sonar point cloud, the method comprising: obtaining underwater sonar data; performing coordinate conversion on the sonar data to obtain underwater point cloud; eliminating outliers in the underwater point cloud to obtain candidate point cloud; obtaining key point sets of different scanning angles according to the candidate point cloud; interpolating the key point set to obtain an interpolation set; performing B-spline surface interpolation on the interpolation set to obtain an interpolation three-dimensional surface; and obtaining an underwater siltation surface according to the interpolation three-dimensional surface marking. By analyzing the sonar data to obtain an underwater point cloud, and further constructing an underwater three-dimensional surface, the underwater siltation can be measured quickly, with good measurement effect and high measurement efficiency, and can be widely used in the technical field of siltation monitoring based on sonar point cloud.

Description

Technical Field

[0001] The present invention relates to the technical field of siltation monitoring, and in particular to a siltation monitoring method, equipment and medium based on sonar point cloud. Background Art

[0002] The increasing siltation in the river has seriously affected the normal functioning of the river, such as flood control, drainage, irrigation, water supply, and navigation. In order to restore the normal function of the river, river dredging projects are often required. For silt of a certain thickness, regular dredging is required to ensure the normal functioning of the river. Therefore, it is necessary to detect the siltation in the river and measure the siltation of the open channel and culvert.

[0003] The existing technology generally uses underwater camera methods and underwater laser imaging methods to measure silt. The detection results of the underwater camera method rely on the camera imaging effect and are greatly restricted by the water quality conditions, resulting in poor measurement results. The laser of the underwater laser imaging method will scatter in the water, resulting in large energy loss and a small imaging range. It can only be used for fixed-point inspection, not large-area inspection, and has low measurement efficiency. Summary of the invention

[0004] In view of this, the purpose of the embodiments of the present invention is to provide a siltation monitoring method, equipment and medium based on sonar point cloud, which can quickly measure underwater siltation, thereby monitoring underwater silt, with good measurement effect and high measurement efficiency.

[0005] In a first aspect, an embodiment of the present invention provides a method for monitoring siltation based on sonar point cloud, comprising:

[0006] Obtain underwater sonar data;

[0007] Performing coordinate transformation on the sonar data to obtain an underwater point cloud;

[0008] Eliminating outlier points in the underwater point cloud to obtain a candidate point cloud;

[0009] Acquire a set of key points at different scanning angles according to the candidate point cloud, wherein the scanning angle represents the position information of the sonar device;

[0010] After interpolating the key point set, an interpolation set is obtained, and all points in the interpolation set constitute an interpolation curve in a coordinate system;

[0011] The interpolation set is interpolated using B-spline surface to obtain an interpolation three-dimensional surface, wherein the interpolation three-dimensional surface represents an underwater siltation surface.

[0012] In some optional embodiments, the step of performing coordinate conversion on the sonar data to obtain an underwater point cloud includes:

[0013] Acquire a first data point set corresponding to different vertical rotation angles, where the vertical rotation angle represents a vertical rotation angle of the sonar device based on a horizontal plane;

[0014] Converting the first data point set into a coordinate point set in a coordinate system;

[0015] The coordinate point set is marked in a coordinate system to obtain the underwater point cloud.

[0016] In some optional embodiments, converting the first data point set into a coordinate point set in a coordinate system includes:

[0017] Acquire a scanning depth and scanning points of the sonar device, wherein the scanning points are distributed on a scanning beam at the scanning depth;

[0018] Acquire a rotation angle of the sonar device, wherein the rotation angle includes a vertical rotation angle and a horizontal rotation angle;

[0019] The coordinate point set is calculated according to the first data point set, the scanning depth and the rotation angle.

[0020] In some optional embodiments, removing outliers in the underwater point cloud to obtain a candidate point cloud includes:

[0021] Obtaining a neighborhood of each point in the underwater point cloud;

[0022] Calculate the average distance of each of the neighborhoods, the average distance represents the average distance from other points in the neighborhood to the source point, and the neighborhood represents the area constructed around the source point;

[0023] Calculate the standard deviation based on the average distance;

[0024] Determine the outlier point according to the average distance, the standard deviation and a preset standard deviation multiple;

[0025] The candidate point cloud is obtained after deleting the outlier points.

[0026] In some optional embodiments, determining the outlier according to the average distance, the standard deviation, and a preset standard deviation multiple includes:

[0027] Obtaining a convergence distance according to the standard deviation and the preset standard deviation multiple;

[0028] Obtaining the average distance corresponding to each point in the underwater point cloud;

[0029] Points whose average distance is greater than the convergence distance are configured as outliers.

[0030] In some optional embodiments, acquiring key point sets at different scanning angles according to the candidate point cloud includes:

[0031] Acquire a second set of data points at different scanning angles according to the candidate point cloud and an intensity threshold, wherein the intensity threshold represents an energy intensity threshold of the data point;

[0032] Calculating the mean intensity of all data points in the second data point set;

[0033] Compare the intensity values ​​of all data points in the second data point set with the intensity mean, and obtain the data point whose intensity value has the smallest difference with the intensity mean;

[0034] The data point whose intensity value differs the least from the intensity mean is configured as a key point;

[0035] The key points corresponding to different scanning angles are combined into the key point set.

[0036] In some optional embodiments, the interpolating the key point set to obtain an interpolation set includes:

[0037] Dividing the key point set into a plurality of sub-intervals;

[0038] Calculating a first interpolation function according to the key points of the subinterval;

[0039] splicing the first interpolation functions of a plurality of the subintervals to obtain a second interpolation function;

[0040] The function points of the second interpolation function constitute the interpolation set.

[0041] In some optional embodiments, performing B-spline surface interpolation on the interpolation set to obtain an interpolated three-dimensional surface includes:

[0042] Get several data points in the interpolation set;

[0043] Performing cubic B-spline surface interpolation on a number of the data points to obtain a surface control point set;

[0044] The interpolated three-dimensional surface is constructed by using the surface control point set.

[0045] In a second aspect, an embodiment of the present invention provides a computer device, comprising a processor, a memory, and a computer program stored in the memory and executable by the processor, wherein the steps of the above method are implemented when the computer program is executed by the processor.

[0046] In a third aspect, an embodiment of the present invention provides a computer-readable storage medium, in which a program executable by a processor is stored. When the program executable by the processor is executed by the processor, it is used to perform the method as described above.

[0047] Implementation of the embodiments of the present invention includes the following beneficial effects: the embodiments of the present invention provide a siltation monitoring method based on sonar point cloud, including: acquiring underwater sonar data; performing coordinate transformation on the sonar data to obtain an underwater point cloud; eliminating outliers in the underwater point cloud to obtain a candidate point cloud; acquiring a key point set at different scanning angles according to the candidate point cloud, the scanning angle representing the position information of the sonar device; interpolating the key point set to obtain an interpolation set, all points in the interpolation set forming an interpolation curve in the coordinate system; performing B-spline surface interpolation on the interpolation set to obtain an interpolated three-dimensional surface, the interpolated three-dimensional surface representing the underwater siltation surface. Underwater point clouds are obtained by analyzing underwater sonar data, and outliers in the underwater point clouds are eliminated. Key points at each scanning angle are obtained according to the intensity threshold, and the key points are interpolated to construct a smooth interpolation curve to reduce noise and discontinuity in the point cloud. The interpolation curve at each scanning angle is interpolated using B-spline surfaces to construct an underwater three-dimensional surface, so as to quickly measure underwater siltation and monitor underwater silt, with good measurement effect and high measurement efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0048] Figure 1 is a flow chart of a siltation monitoring method based on sonar point cloud provided by an embodiment of the present invention;

[0049] Figure 2 is a model diagram of a swimming pool provided by an embodiment of the present invention;

[0050] Figure 3 is a two-dimensional sonar image of a swimming pool provided by an embodiment of the present invention;

[0051] Figure 4 is an interpolated three-dimensional surface diagram of a swimming pool provided by an embodiment of the present invention;

[0052] Figure 5 It is a schematic block diagram of the structure of a computer device provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0053] Embodiments of the present invention are described in detail below, and examples of the embodiments are shown in the accompanying drawings, wherein the same or similar reference numerals throughout represent the same or similar elements or elements having the same or similar functions. The embodiments described below with reference to the accompanying drawings are exemplary and are only used to explain the present invention, and cannot be understood as limiting the present invention.

[0054] In the description of the present invention, it should be understood that descriptions involving orientation, such as up, down, front, back, left, right, etc., indicating orientations or positional relationships, are based on the orientations or positional relationships shown in the accompanying drawings, and are only for the convenience of describing the present invention and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore should not be understood as a limitation on the present invention.

[0055] In the description of the present invention, "several" means one or more, "more" means more than two, "greater than", "less than", "exceed" etc. are understood as not including the number itself, and "above", "below", "within" etc. are understood as including the number itself. If there is a description of "first" or "second", it is only used for the purpose of distinguishing the technical features, and cannot be understood as indicating or implying the relative importance or implicitly indicating the number of the indicated technical features or implicitly indicating the order of the indicated technical features.

[0056] In the description of the present invention, unless otherwise clearly defined, terms such as setting, installing, connecting, etc. should be understood in a broad sense, and technicians in the relevant technical field can reasonably determine the specific meanings of the above terms in the present invention based on the specific content of the technical solution.

[0057] The following further describes the siltation monitoring method based on sonar point cloud according to an embodiment of the present invention.

[0058] Reference Figure 1 , Figure 1 A flow chart of a siltation monitoring method based on sonar point cloud provided by an embodiment of the present invention, the siltation monitoring method based on sonar point cloud includes but is not limited to the following steps:

[0059] S101, acquiring underwater sonar data;

[0060] S102, performing coordinate conversion on the sonar data to obtain an underwater point cloud;

[0061] S103, removing outlier points in the underwater point cloud to obtain a candidate point cloud;

[0062] S104, acquiring a set of key points at different scanning angles according to the candidate point cloud, wherein the scanning angle represents the position information of the sonar device;

[0063] S105, interpolating the key point set to obtain an interpolation set, where all points in the interpolation set form an interpolation curve in a coordinate system;

[0064] S106, performing B-spline surface interpolation on the interpolation set to obtain an interpolated three-dimensional surface, wherein the interpolated three-dimensional surface represents an underwater siltation surface.

[0065] It is worth noting that the sonar data of the present application is obtained through sonar equipment, and the objects collected can be underwater siltation of rivers, dams, etc., which are not specifically limited here. Underwater siltation can be silt, stones and other debris. The intensity information in the sonar data is that the sonar collects data through the principle of acoustic propagation. After the sound waves emitted by the sonar encounter an object, a stronger energy value is generated here and returned. This energy value is considered as intensity information, and different data points have corresponding energy values. The place where the data point energy value is higher in the river channel is the contour and bottom of the river channel. Each high intensity value point can be converted into (x, y, z) coordinates to obtain an underwater point cloud. The sonar data includes the intensity information of the river channel at different scanning angles. Different scanning angles indicate that the probe of the sonar equipment is at different angles. When collecting data, the sonar collects data while rotating the angle of the probe. After the collection at one angle is completed, it is necessary to continue to rotate the angle to collect sonar data at other positions in the river channel. The interpolated three-dimensional surface represents the surface of the sediment in the river channel. The sediment can be silt, stones and other debris, which are not limited here.

[0066] It should be noted that this application uses underwater sonar data of rivers, dams, etc. collected by sonar equipment, and this application takes rivers as an example. The sonar data contains the intensity information of the river; the intensity information of the river is then converted into point information stored in a Cartesian coordinate system (the specific coordinates are not limited here) to form an underwater point cloud. The underwater point clouds at different scanning angles are preprocessed to remove outliers to obtain candidate point clouds at different angles. All data points at different scanning angles in the candidate point cloud are obtained, and several data points of a certain scanning angle are filtered out according to a given intensity threshold. The filtered data points are calculated and processed to obtain key points. The key points at different scanning angles constitute a key point set. ; Use piecewise quadratic interpolation to Interpolate all points in to get the interpolation set , so that the discrete points are interpolated into a smooth interpolation curve in the coordinate system; for all the above , using B-spline surface interpolation, construct a three-dimensional interpolation surface , interpolating three-dimensional surfaces Mark the underwater siltation surface to obtain the depth of sediments such as silt, so as to monitor the underwater siltation situation in real time and visually.

[0067] In some optional embodiments, Figure 1 The step 102 shown includes but is not limited to: obtaining a first set of data points corresponding to different vertical rotation angles, wherein the vertical rotation angle represents the vertical rotation angle of the sonar device based on the horizontal plane; converting the first set of data points into a set of coordinate points in a coordinate system; and marking the set of coordinate points in the coordinate system to obtain the underwater point cloud.

[0068] Specifically, the sonar data is collected as riverbed intensity information at multiple different vertical rotation angles, and a corresponding first data point set is obtained according to the riverbed intensity information at each vertical rotation angle. Specifically, points whose intensity values ​​represented by the riverbed intensity information are greater than a preset value are marked as data points, and the data points in the data point set are converted into point information of a Cartesian coordinate system to form an underwater point cloud. , where i represents the i-th vertical rotation angle. The intensity information of the river bottom includes several points whose intensity values ​​are greater than the preset value, and the greater the intensity value returned in a certain area, the higher the density of the points.

[0069] In some optional embodiments, converting the first data point set into a coordinate point set in a coordinate system includes: obtaining a scanning depth and scanning points of the sonar device, wherein the scanning points are distributed on a scanning beam of the scanning depth; obtaining a rotation angle of the sonar device, wherein the rotation angle includes a vertical rotation angle and a horizontal rotation angle; and calculating the coordinate point set according to the first data point set, the scanning depth, and the rotation angle.

[0070] Specifically, the input sonar data is parsed to calculate the first data point set of the current sonar, which includes data points at different vertical rotation angles, and the preset sonar scanning depth is obtained according to the sonar acquisition principle. , evenly distributed on the scanning beam at this scanning depth points, and convert the data points into a set of coordinate points in a rectangular coordinate system through the relationship between the angle value and the distance value. , i represents the i-th vertical rotation angle, and the calculation formula of the specific coordinate point is as follows:

[0071]

[0072] in, represents the first rotation angle sampling points (data points), Expressed as The distance from the sampling point to the sonar transmitting point, It is expressed as the vertical rotation angle value of the sonar probe in the sonar device. It is expressed as the horizontal rotation angle value of the sonar probe. For the The coordinates of the sampling points.

[0073] By calculating the coordinate values ​​of all sampling points under the i-th vertical rotation angle, the coordinate point set is obtained. , the corresponding underwater point cloud is obtained by marking in the coordinate system, and the coordinate point sets at different angles are calculated. After marking in the coordinate system, the overall underwater point cloud is obtained.

[0074] In some optional embodiments, Figure 1 Step 103 shown includes but is not limited to: obtaining the neighborhood of each point in the underwater point cloud; calculating the average distance of each of the neighborhoods, the average distance representing the average distance from other points in the neighborhood to the source point, and the neighborhood representing the area constructed around the source point; calculating the standard deviation based on the average distance; determining the outlier points based on the average distance, the standard deviation and a preset standard deviation multiple; and obtaining the candidate point cloud after deleting the outlier points.

[0075] Specifically, calculate the distance from each point in the underwater point cloud to its nearest The average distance between each point and its nearest The area of ​​each point constitutes a neighborhood, and the average distance of the neighborhood of all points in the point cloud constitutes a Gaussian distribution. Statistical analysis is performed on the neighborhood of each point to determine the corresponding outliers, and the outliers are deleted to obtain the candidate point cloud after filtering and denoising.

[0076] In some optional embodiments, the determining of the outlier points based on the average distance, the standard deviation and the preset standard deviation multiple includes: obtaining the convergence distance based on the standard deviation and the preset standard deviation multiple; obtaining the average distance corresponding to each point in the underwater point cloud; and configuring the points whose average distance is greater than the convergence distance as outliers.

[0077] Specifically, the first The coordinates of the points are , No. In the neighborhood of a point The coordinates of the points are , the distance between the two points is :

[0078] Calculate the number of points in the nth order to its neighborhood The average distance between any points , expressed as:

[0079] A neighborhood is constructed for all points in the underwater point cloud to solve the average distance in its neighborhood. If the underwater point cloud includes one thousand points, the average distance corresponding to one thousand points is obtained. The average distance of all the obtained points is averaged to obtain the average distance of the underwater point cloud, and the standard deviation of the average distance of the underwater point cloud is obtained to establish a Gaussian distribution, and the preset standard deviation multiple is obtained. The standard deviation multiplied by the preset standard deviation multiple is used as the convergence distance; the average distance corresponding to the point in the underwater point cloud is compared with the convergence distance, and the points with an average distance greater than the convergence distance are deleted as outliers, thereby obtaining a candidate point cloud.

[0080] In some optional embodiments, Figure 1 Step 104 shown includes but is not limited to: obtaining a second set of data points at different scanning angles based on the candidate point cloud and an intensity threshold, wherein the intensity threshold represents an energy intensity threshold of the data point; calculating the intensity mean of all data points in the second set of data points; comparing the intensity values ​​of all data points in the second set of data points with the intensity mean to obtain the data point whose intensity value differs minimally from the intensity mean; configuring the data point whose intensity value differs minimally from the intensity mean as a key point; and forming the key points corresponding to different scanning angles into the key point set.

[0081] Specifically, for the first Vertical rotation angle All data points of horizontal rotation angles are selected according to the given intensity threshold to form a data point set of five points (the specific number of points is set according to requirements) , calculate the intensity mean of the filtered data points , find the point set The point with medium intensity value closest to the mean , as the key point at this angle, store all key points at different angles into the key point set middle.

[0082] It is expressed as:

[0083] in, Represents the intensity value of the hth point.

[0084] In some optional embodiments, Figure 1 The step 105 shown includes but is not limited to: dividing the key point set into a number of sub-intervals; calculating a first interpolation function based on the key points of the sub-intervals; concatenating the first interpolation functions of a number of the sub-intervals to obtain a second interpolation function; and the function points of the second interpolation function constitute the interpolation set.

[0085] Specifically, for the key point set Segment to obtain multiple sub-intervals, specifically every three nodes (that is, Three consecutive key points in the interval (the specific number of key points is determined by the interpolation type) are a subinterval. , is the total number of subintervals;

[0086] According to the sub-interval Three nodes of , , calculate the The first interpolation function of the subinterval :

[0087]

[0088]

[0089] in, Is a node On the horizontal axis The ordinate value corresponding to the location;

[0090] The interpolation functions of all sub-intervals are stitched together to form the second interpolation function on the entire interval :

[0091]

[0092] in, Represents the horizontal coordinates of all data points in the interval (that is, the horizontal coordinates of the key points), Represents the number of all data points in this interval.

[0093] The second interpolation function The function value interval on the interval constitutes the interpolation set The second interpolation function It is a smooth interpolation curve in the coordinate system.

[0094] Figure 1 The interpolation three-dimensional surface is obtained by performing B-spline surface interpolation on the interpolation set in step 106 shown, including but not limited to: obtaining a number of data points in the interpolation set; performing cubic B-spline surface interpolation on the data points to obtain a surface control point set; and constructing the interpolation three-dimensional surface through the surface control point set.

[0095] Specifically, get the interpolation set Data points ,in and c, whose parameter range is 1 and 1, 1 and 1 are all constant values ​​and have no practical meaning; the node vector is and , at the data point It can be expressed as:

[0096]

[0097] in, Represents the number of data points in the vertical direction, Represents the number of data points in the horizontal direction, and are respectively direction( direction) and direction( direction), and Respectively Direction and The node vector of the direction; Indicates that the surface is in the parameter and The position below; is B-spline basis functions in directions; is B-spline basis functions in directions; is the control point, indicating the position in three-dimensional space;

[0098] Will fixed, It can also be expressed as:

[0099]

[0100]

[0101] in,

[0102]

[0103] yes data points, yes data points;

[0104] Using node vector and parameters 1 Do Subcurve interpolation: For , respectively construct interpolation at points The curve of ; Use node vector and parameters 1 Do Subcurve interpolation: For , respectively construct interpolation at points The curve is used to obtain the control points of the surface , the control points generated by Construct the final interpolated surface , that is, to obtain an interpolated three-dimensional surface. According to the terrain of the bottom three-dimensional surface, the elevation of the constructed three-dimensional interpolated cloud surface to the scanning sonar can reflect the distance from the underwater siltation to the scanning sonar, thereby monitoring whether the bottom siltation affects the operation of dams, rivers, etc.

[0105] Reference Figure 2 , taking a certain on-site swimming pool as an example, Figure 3 This is a single-angle two-dimensional sonar image obtained by sonar scanning the swimming pool. Figure 4 The model diagram of the interpolated three-dimensional surface is finally constructed by curve interpolation and surface interpolation of the data points obtained after the sonar image is analyzed. The method of the present invention can convert the sonar scanning data into three-dimensional point cloud data and basically restore the three-dimensional surface of the underwater siltation surface. By using the elevation of the constructed interpolated three-dimensional surface to the scanning sonar, the distance from the underwater siltation to the scanning sonar can be reflected, so as to monitor whether the siltation affects the normal operation of dams, rivers, etc., and effectively, in real time, and visually monitor the underwater siltation situation.

[0106] This embodiment uses a swimming pool as a simulation. First, because the swimming pool is basically noise-free and the scanning situation is clear, and second, the underwater situation of the swimming pool is visible. Choosing a swimming pool as a simulation can check whether the method of the present application can convert the sonar scan image into a corresponding three-dimensional surface image. The siltation situation after the sonar scan will be displayed on the sonar image and the data will be returned. The returned data is analyzed to see whether it can match the sonar scan image. Choosing a swimming pool as a test not only checks whether the sonar scan image is correct (because the swimming pool is visible, so it is possible to check whether the sonar scan image is correct), but also checks whether the interpolated three-dimensional surface obtained by the present application can correspond to the sonar scan image, because the sonar needs to scan a certain distance. If a river channel with a suitable depth is selected, the underwater situation is unknown and cannot be detected.

[0107] Implementation of the embodiments of the present invention includes the following beneficial effects: the embodiments of the present invention provide a siltation monitoring method based on sonar point cloud, including: acquiring underwater sonar data; performing coordinate transformation on the sonar data to obtain an underwater point cloud; eliminating outliers in the underwater point cloud to obtain a candidate point cloud; acquiring a key point set at different scanning angles according to the candidate point cloud, the scanning angle representing the position information of the sonar device; interpolating the key point set to obtain an interpolation set, all points in the interpolation set forming an interpolation curve in the coordinate system; performing B-spline surface interpolation on the interpolation set to obtain an interpolated three-dimensional surface, the interpolated three-dimensional surface representing the underwater siltation surface. Underwater point clouds are obtained by analyzing underwater sonar data, and outliers in the underwater point clouds are eliminated. Key points at each scanning angle are obtained according to the intensity threshold, and the key points are interpolated to construct a smooth interpolation curve to reduce noise and discontinuity in the point cloud. The interpolation curve at each scanning angle is interpolated using B-spline surfaces to construct an underwater three-dimensional surface, so as to quickly measure underwater siltation and monitor underwater silt, with good measurement effect and high measurement efficiency.

[0108] The present invention aims at the problem that the existing sediment deposition measurement method may not be able to effectively visualize the underwater structure when the underwater situation is complicated. The present invention first inputs the sonar scanning data and parses and converts it into point cloud data in a Cartesian coordinate system, then selects a suitable frequency filter, obtains key points by giving an intensity threshold, and then performs piecewise quadratic interpolation to construct a smooth curve, and finally constructs a three-dimensional surface of the underwater situation of the river channel by cubic B-spline surface interpolation.

[0109] The underwater siltation is measured by sonar scanning. At the same time, sonar can realize multi-angle measurement and measure multiple sets of siltation information to draw a three-dimensional surface of the underwater siltation surface based on the siltation information. The three-dimensional surface of the underwater siltation surface is constructed by converting two-dimensional coordinates into three-dimensional coordinates. The elevation from the constructed three-dimensional point cloud surface to the scanning sonar can reflect the distance from the underwater siltation to the scanning sonar, thereby monitoring whether the siltation affects the normal operation of the dam or river channel.

[0110] like Figure 5As shown, in the second aspect, an embodiment of the present invention further provides a computer device, which can be a terminal. The computer device includes a processor, a memory, and a network interface connected via a system bus, wherein the memory may include a non-volatile storage medium and an internal memory. The non-volatile storage medium can store an operating system and a computer program. The computer program includes program instructions, which, when executed, enable the processor to execute any one of the methods for visualizing management of industrial equipment. The processor is used to provide computing and control capabilities to support the operation of the entire computer device. The internal memory provides an environment for the operation of the computer program in the non-volatile storage medium, which, when executed by the processor, enables the processor to execute any one of the methods for visualizing management of industrial equipment. The network interface is used for network communications, such as sending assigned tasks, etc. Those skilled in the art will appreciate that Figure 5 The structure shown in the figure is only a block diagram of a part of the structure related to the solution of the present disclosure, and does not constitute a limitation on the computer device to which the solution of the present disclosure is applied. The specific computer device may include Figure 5 More or less components shown in, or some components are combined, or there are different component arrangements. It should be understood that the processor can be a central processing unit (CPU), and the processor can also be other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field programmable gate arrays (FPGA) or other programmable logic devices, discrete gates or transistor logic devices, discrete hardware components, etc. Among them, the general-purpose processor can be a microprocessor or the processor can also be any conventional processor, etc. In one embodiment, the processor is used to run a computer program stored in a memory to implement the following steps: acquiring underwater sonar data; performing coordinate transformation on the sonar data to obtain an underwater point cloud; eliminating outliers in the underwater point cloud to obtain a candidate point cloud; acquiring a key point set at different scanning angles based on the candidate point cloud, wherein the scanning angle represents the position information of the sonar device; interpolating the key point set to obtain an interpolation set, wherein all points in the interpolation set constitute an interpolation curve in the coordinate system; performing B-spline surface interpolation on the interpolation set to obtain an interpolated three-dimensional surface, wherein the interpolated three-dimensional surface represents the underwater siltation surface.

[0111] It can be seen that the contents of the above method embodiments are all applicable to the present device embodiments, the functions specifically implemented by the present device embodiments are the same as those of the above method embodiments, and the beneficial effects achieved are also the same as those achieved by the above method embodiments.

[0112] In addition, the embodiment of the present application also discloses a computer program product or a computer program, and the computer program product or the computer program is stored in a computer-readable storage medium. The processor of the computer device can read the computer program from the computer-readable storage medium, and the processor executes the computer program, so that the computer device performs the above method. Similarly, the contents in the above method embodiment are all applicable to the storage medium embodiment, and the functions specifically implemented by the storage medium embodiment are the same as those in the above method embodiment, and the beneficial effects achieved are also the same as those achieved by the above method embodiment.

[0113] It is understood that all or some steps and systems in the disclosed method above can be implemented as software, firmware, hardware and appropriate combinations thereof. Some physical components or all physical components can be implemented as software executed by a processor, such as a central processing unit, a digital information processor or a microprocessor, or implemented as hardware, or implemented as an integrated circuit, such as an application-specific integrated circuit. Such software can be distributed on a computer-readable medium, and the computer-readable medium can include a computer storage medium (or a non-transitory medium) and a communication medium (or a temporary medium). As known to those of ordinary skill in the art, the term computer storage medium includes volatile and non-volatile, removable and non-removable media implemented in any method or technology for storing information (such as computer-readable instructions, data structures, program modules or other data). Computer storage media include, but are not limited to, RAM, ROM, EEPROM, flash memory or other memory technology, CD-ROM, digital versatile disk (DVD) or other optical disk storage, magnetic cassette, magnetic tape, disk storage or other magnetic storage device, or any other medium that can be used to store desired information and can be accessed by a computer. Furthermore, it is well known to those skilled in the art that communication media generally contain computer readable instructions, data structures, program modules, or other data in modulated data information such as carrier waves or other transport mechanisms, and may include any information delivery media.

[0114] The embodiments of the present invention are described in detail above with reference to the accompanying drawings, but the present invention is not limited to the above embodiments, and various changes can be made within the knowledge scope of ordinary technicians in the technical field without departing from the purpose of the present invention.

Claims

1. A siltation monitoring method based on sonar point cloud, characterized in that: include: Obtain underwater sonar data; Performing coordinate transformation on the sonar data to obtain an underwater point cloud; Specifically, the method includes: obtaining a first data point set corresponding to different vertical rotation angles, wherein the vertical rotation angle represents a vertical rotation angle of the sonar device based on a horizontal plane; converting the first data point set into a coordinate point set in a coordinate system; and annotating the coordinate point set in the coordinate system to obtain the underwater point cloud; Eliminate outliers in the underwater point cloud to obtain a candidate point cloud; specifically include: obtaining a neighborhood of each point in the underwater point cloud; calculating an average distance of each of the neighborhoods, the average distance representing the average distance from other points in the neighborhood to the source point, the neighborhood representing the area constructed around the source point; calculating a standard deviation based on the average distance; determining the outliers based on the average distance, the standard deviation and a preset standard deviation multiple; and obtaining the candidate point cloud after deleting the outliers; Acquire a key point set at different scanning angles according to the candidate point cloud, wherein the scanning angle represents the position information of the sonar device; the acquisition of the key point set at different scanning angles according to the candidate point cloud comprises: acquiring a second data point set at different scanning angles according to the candidate point cloud and an intensity threshold, wherein the intensity threshold represents the energy intensity threshold of the data point; calculating the intensity mean of all data points in the second data point set; comparing the intensity values ​​of all data points in the second data point set with the intensity mean to obtain the data point with the smallest difference between the intensity value and the intensity mean; configuring the data point with the smallest difference between the intensity value and the intensity mean as a key point; and composing the key points corresponding to different scanning angles into the key point set; After interpolating the key point set, an interpolation set is obtained, and all points in the interpolation set constitute an interpolation curve in a coordinate system; The interpolation set is interpolated using B-spline surface to obtain an interpolation three-dimensional surface, wherein the interpolation three-dimensional surface represents an underwater siltation surface.

2. The method according to claim 1, characterized in that The converting the first data point set into a coordinate point set in a coordinate system includes: Acquire a scanning depth and scanning points of the sonar device, wherein the scanning points are distributed on a scanning beam at the scanning depth; Acquire a rotation angle of the sonar device, wherein the rotation angle includes a vertical rotation angle and a horizontal rotation angle; The coordinate point set is calculated according to the first data point set, the scanning depth and the rotation angle.

3. The method according to claim 1, characterized in that The determining the outlier according to the average distance, the standard deviation and a preset standard deviation multiple includes: Obtaining a convergence distance according to the standard deviation and the preset standard deviation multiple; Obtaining the average distance corresponding to each point in the underwater point cloud; Points whose average distance is greater than the convergence distance are configured as outliers.

4. The method according to claim 1, characterized in that: The interpolation set is obtained after interpolating the key point set, including: Dividing the key point set into a plurality of sub-intervals; Calculating a first interpolation function according to the key points of the subinterval; splicing the first interpolation functions of a plurality of the subintervals to obtain a second interpolation function; The function points of the second interpolation function constitute the interpolation set.

5. The method according to claim 1, characterized in that The step of performing B-spline surface interpolation on the interpolation set to obtain an interpolated three-dimensional surface comprises: Get several data points in the interpolation set; Performing cubic B-spline surface interpolation on a number of the data points to obtain a surface control point set; The interpolated three-dimensional surface is constructed by using the surface control point set.

6. A computer device, wherein: The computer device comprises a processor, a memory, and a computer program stored in the memory and executable by the processor, wherein when the computer program is executed by the processor, the steps of the method according to any one of claims 1 to 5 are implemented.

7. A computer-readable storage medium storing a program executable by a processor, characterized in that: The processor-executable program is used to perform the method according to any one of claims 1 to 5 when executed by the processor.

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