Section flow obtaining method and device, computer equipment and storage medium

Abstract

The invention relates to the technical field of profile flow measurement, in particular to a profile flow obtaining method and device, computer equipment and a storage medium, and the method comprises the steps: obtaining the measurement flow velocity data of a plurality of profiles of a to-be-measured river section, and determining the center points of the plurality of profiles according to the three-dimensional coordinates of a plurality of points in the measurement flow velocity data of the plurality of profiles; according to the central points of the plurality of sections, constructing a vertical plane in the flow velocity direction as a unified plane of the to-be-measured river section; according to the measured flow velocity data of the plurality of sections, performing vertical mapping on a unified plane of the to-be-measured river section to obtain unified plane flow velocity data of the plurality of sections; performing blind area data prediction and data completion processing on the unified plane flow velocity data of the plurality of sections to obtain the unified plane flow velocity data of the plurality of sections after completion processing; and performing flow calculation according to the unified plane flow velocity data of the plurality of complemented sections to obtain section flow data of the to-be-measured river section.

Description

Technical Field

[0001] The present invention relates to the technical field of cross-sectional flow measurement, and particularly to a method, device, computer device and storage medium for obtaining cross-sectional flow. Background Art

[0002] With the rapid development of the economy, the demand for water resources has been increasing year by year, and the problem of water resource shortage has become increasingly prominent. In order to rationally utilize and protect water resources, ensure the sustainable development of water resources, improve the level of water resource management and utilization efficiency, the accurate measurement of flow rate is particularly important. Cross-sectional flow measurement, as an important means for monitoring water resources and pollution fluxes, is of great significance for mastering the river water quality and water resource status, formulating water resource development and utilization plans, and ensuring water environment safety.

[0003] Traditional cross-sectional flow measurement methods mainly include current meter method, float method, ultrasonic method, etc. These methods can meet the requirements of flow measurement to a certain extent, but there are certain limitations, such as low measurement accuracy, large influence by the environment, poor real-time performance, etc. In order to improve the accuracy and real-time performance of cross-sectional flow measurement, an acoustic Doppler current profiler (ADCP) is introduced for flow measurement. Using ADCP for cross-sectional flow measurement has the characteristics of high precision, fast speed, real-time, etc., which helps to improve the level of water resource management. With the continuous improvement of the water resource management requirements in China, the application of ADCP in cross-sectional flow measurement will be more and more extensive, contributing to water resource protection and sustainable development. However, restricted by practical factors such as hydrological fluctuations, echo quality, measurement requirements, and equipment safety, there are problems in ADCP cross-sectional flow measurement, such as it is difficult to maintain a unified measurement profile for multiple measurements, the equipment cannot fully measure the near-shore flow velocities on both sides, the echo signal quality at the near-bottom is poor and the flow velocity cannot be calculated, and there are measurement blind areas near the surface due to the equipment draft depth and accuracy limitations. These limit the stability, accuracy and reliability of ADCP cross-sectional flow measurement. Summary of the Invention

[0004] Based on this, the purpose of the present invention is to provide a method, device, computer device and storage medium for obtaining cross-sectional flow. By performing unified planar flow velocity data conversion, blind area prediction and data complementation processing on the measured flow velocity data of multiple profiles, complete unified planar flow velocity data is obtained for flow calculation, improving the stability, accuracy and reliability of the cross-sectional flow data calculation of river cross-sections.

[0005] In a first aspect, an embodiment of the present application provides a method for obtaining cross-sectional flow, including the following steps:

[0006] Obtain the measured flow velocity data of several profiles of a river cross-section to be measured, where the measured flow velocity data includes the three-dimensional coordinates, flow velocities and flow velocity directions of several points on the profile;

[0007] Determine the center points of several profiles based on the three-dimensional coordinates of several points in the measured flow velocity data of several profiles; construct a vertical plane in the flow velocity direction based on the center points of several profiles as the unified plane of the river section to be measured;

[0008] Perform a vertical mapping from the measured flow velocity data of several profiles to the unified plane of the river section to be measured to obtain the unified plane flow velocity data of several profiles;

[0009] Perform blind area data prediction and data completion processing on the unified plane flow velocity data of several profiles to obtain the unified plane flow velocity data of several profiles after completion processing;

[0010] Calculate the flow rate based on the unified plane flow velocity data of several profiles after completion processing to obtain the profile flow rate data of the river section to be measured.

[0011] In a second aspect, an embodiment of the present application provides a profile flow rate obtaining device, including:

[0012] A data acquisition module for obtaining the measured flow velocity data of several profiles of the river section to be measured, where the measured flow velocity data includes the three-dimensional coordinates, flow velocity, and flow velocity direction of several points on the profile;

[0013] A unified plane construction module for determining the center points of several profiles based on the three-dimensional coordinates of several points in the measured flow velocity data of several profiles; constructing a vertical plane in the flow velocity direction based on the center points of several profiles as the unified plane of the river section to be measured;

[0014] A data mapping module for performing a vertical mapping from the measured flow velocity data of several profiles to the unified plane of the river section to be measured to obtain the unified plane flow velocity data of several profiles;

[0015] A data completion module for performing blind area data prediction and data completion processing on the unified plane flow velocity data of several profiles to obtain the unified plane flow velocity data of several profiles after completion processing;

[0016] A profile flow rate calculation module for calculating the flow rate based on the unified plane flow velocity data of several profiles after completion processing to obtain the profile flow rate data of the river section to be measured.

[0017] In a third aspect, an embodiment of the present application provides a computer device, including: a processor, a memory, and a computer program stored on the memory and executable on the processor; when the computer program is executed by the processor, it implements the steps of the profile flow rate obtaining method as described in the first aspect.

[0018] Fourthly, an embodiment of the present application provides a storage medium storing a computer program, and when the computer program is executed by a processor, the steps of the cross-sectional flow rate obtaining method described in the first aspect are implemented.

[0019] In an embodiment of the present application, a cross-sectional flow rate obtaining method, device, computer device, and storage medium are provided. Based on the hydrological data collected from the river to be measured, by performing unified planar flow velocity data conversion, blind area prediction, and data completion processing on the measured flow velocity data of multiple cross-sections, complete unified planar flow velocity data is obtained for flow rate calculation, improving the stability, accuracy, and reliability of the cross-sectional flow rate data calculation of the river section.

[0020] For better understanding and implementation, the present invention will be described in detail below with reference to the accompanying drawings. Description of the Drawings

[0021] Figure 1 It is a schematic flow chart of the cross-sectional flow rate obtaining method provided by an embodiment of the present application;

[0022] Figure 2 It is a schematic flow chart of S2 in the cross-sectional flow rate obtaining method provided by an embodiment of the present application;

[0023] Figure 3 It is a schematic flow chart of S2 in the cross-sectional flow rate obtaining method provided by an embodiment of the present application;

[0024] Figure 4 It is a schematic flow chart of S3 in the cross-sectional flow rate obtaining method provided by an embodiment of the present application;

[0025] Figure 5 It is a schematic flow chart of S4 in the cross-sectional flow rate obtaining method provided by an embodiment of the present application;

[0026] Figure 6 It is a schematic flow chart of S6 in the cross-sectional flow rate obtaining method provided by another embodiment of the present application;

[0027] Figure 7 It is a schematic flow chart of S5 in the cross-sectional flow rate obtaining method provided by an embodiment of the present application;

[0028] Figure 8 It is a schematic structural diagram of the cross-sectional flow rate obtaining device provided by an embodiment of the present application;

[0029] Figure 9 It is a schematic structural diagram of the computer device provided by an embodiment of the present application. Detailed Embodiments

[0030] Exemplary embodiments will be described in detail herein, and examples thereof are shown in the accompanying drawings. When the following description refers to the accompanying drawings, unless otherwise indicated, the same numbers in different drawings represent the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with the present application. On the contrary, they are merely examples of devices and methods consistent with some aspects of the present application as detailed in the appended claims.

[0031] The terms used in this application are for the purpose of describing specific embodiments only and are not intended to limit the present application. The singular forms "a", "the", and "said" used in this application and the appended claims are also intended to include the plural forms unless the context clearly dictates otherwise. It should also be understood that the term "and / or" as used herein refers to and encompasses any and all possible combinations of one or more of the associated listed items.

[0032] It should be understood that although the terms first, second, third, etc. may be used in this application to describe various information, such information should not be limited to these terms. These terms are only used to distinguish the same type of information from each other. For example, without departing from the scope of the present application, the first information may also be referred to as the second information, and similarly, the second information may also be referred to as the first information. Depending on the context, the word "if" as used herein may be interpreted as "when" or "while" or "in response to determining".

[0033] Please refer to Figure 1 , Figure 1 which is a schematic flow chart of a method for obtaining cross-sectional flow rate provided for an embodiment of the present application. The method includes the following steps:

[0034] S1: Obtain the measured flow velocity data of several cross-sections of the river to be measured.

[0035] The execution subject of the cross-sectional flow rate obtaining method is an obtaining device for the cross-sectional flow rate obtaining method (hereinafter referred to as the obtaining device). In an alternative embodiment, the obtaining device may be a computer device, which may be a server, or a server cluster formed by combining multiple computer devices.

[0036] In this embodiment, the obtaining device obtains the measured flow velocity data of several cross-sections of the river to be measured. Among them, the measured flow velocity data is obtained by measuring the cross-sectional flow velocity data of the same cross-section at least twice in a short term using an acoustic Doppler current profiler; the measured flow velocity data includes the three-dimensional coordinates, flow velocity, and flow velocity direction of several points on the cross-section; the three-dimensional coordinates include horizontal coordinates, vertical coordinates, and elevation coordinates.

[0037] S2: Determine the central points of several profiles based on the three-dimensional coordinates of several points in the measured flow velocity data of the several profiles; construct a vertical plane in the flow velocity direction based on the central points of the several profiles as the unified plane of the river section to be measured.

[0038] In this embodiment, the acquisition device determines the central points of several profiles based on the three-dimensional coordinates of several points in the measured flow velocity data of the several profiles, and constructs a vertical plane in the flow velocity direction based on the central points of the several profiles as the unified plane of the river section to be measured. Among them, determining the central point of the profile includes but is not limited to the geometric center of the three-dimensional profile and the center of the two-dimensional measurement profile based on longitude and latitude.

[0039] Please refer to Figure 2 , Figure 2 which is a schematic flowchart of S2 in the profile flow rate acquisition method provided by an embodiment of the present application, including steps S21 to S22, specifically as follows:

[0040] S21: Obtain the three-dimensional surface geometric center distances of several points of several profiles according to the three-dimensional coordinates of several points in the measured flow velocity data of the several profiles and a preset three-dimensional surface geometric center distance calculation algorithm.

[0041] The three-dimensional surface geometric center distance calculation algorithm is:

[0042]

[0043] In the formula, is the average horizontal coordinate, N is the total number of points in the profile, x i is the horizontal coordinate of the i-th point, is the average vertical coordinate, y i is the vertical coordinate of the i-th point, is the average elevation coordinate, z i is the elevation coordinate of the i-th point, d(x i , y i , z i ) is the three-dimensional surface geometric center distance of the i-th point.

[0044] In this embodiment, the acquisition device adopts a method of vertically mapping a three-dimensional surface to a unified profile, and obtains the three-dimensional surface geometric center distances of several points of several profiles according to the three-dimensional coordinates of several points in the measured flow velocity data of the several profiles and a preset three-dimensional surface geometric center distance calculation algorithm.

[0045] S22: Take the point with the smallest three-dimensional surface geometric center distance among several points of the same profile as the central point of the corresponding profile, and obtain the central points of several profiles.

[0046] In this embodiment, the acquisition device obtains the distances of the geometric centers of the three-dimensional surfaces of several points on the same section, takes the point with the smallest distance of the geometric center of the three-dimensional surface as the center point of the corresponding section, and obtains the center points of several sections.

[0047] Please refer to Figure 3 , Figure 3 which is a schematic flowchart of step S2 in the cross-section flow rate acquisition method provided by an embodiment of the present application, including step S23, specifically as follows:

[0048] S23: Obtain the average flow velocity direction of the unit range area of the center points of several sections, and construct a vertical plane of the flow velocity direction according to the three-dimensional coordinates of the center points of several sections and the average flow velocity direction of the unit range area.

[0049] In this embodiment, the acquisition device obtains the average flow velocity direction of the unit range area of the center points of several sections, and constructs a vertical plane of the flow velocity direction according to the three-dimensional coordinates of the center points of several sections and the average flow velocity direction of the unit range area.

[0050] S3: Make a vertical mapping of the measured flow velocity data of several sections to the unified plane of the cross-section of the river to be measured, and obtain the unified plane flow velocity data of several sections.

[0051] In this embodiment, the acquisition device makes a vertical mapping of the measured flow velocity data of several sections to the unified plane of the cross-section of the river to be measured, and obtains the unified plane flow velocity data of several sections. The curved measurement sections can be processed into a unified section perpendicular to the flow velocity direction, reducing the measurement error and improving the reliability of the flow rate result. Among them, the methods for calculating the unified plane flow velocity data include, but are not limited to, the vertical mapping method of the three-dimensional surface to the unified section and the two-dimensional mapping method based on longitude and latitude.

[0052] Please refer to Figure 4 , Figure 4 which is a schematic flowchart of step S3 in the cross-section flow rate acquisition method provided by an embodiment of the present application, including step S31, specifically as follows:

[0053] S31: Adopt the three-dimensional surface vertical mapping method, and construct a vertical mapping from several points of several sections to the unified plane according to the three-dimensional coordinates, flow velocity and flow velocity direction of several points in the measured flow velocity data of several sections, so as to obtain the unified plane flow velocity data of several sections.

[0054] In this embodiment, the acquisition device adopts the three-dimensional surface vertical mapping method. Suppose the surface is described by the parametric equation described, and the plane is described by the equation Ax + By + Cz + D = 0, where A, B, C, D are constants, and A 2 +B2 +C 2 ≠0, where x is the horizontal coordinate, y is the vertical coordinate, z is the elevation coordinate, u is the flow velocity variable, and v is the flow velocity direction variable.

[0055] For any point on the surface The acquisition device calculates the plane normal vector And calculates the directed distance formula from this point to the unified plane Where Is the normal vector Of the Euclidean norm, d is the directed distance. The acquisition device constructs a vertical mapping from several points on several profiles to the unified plane based on the three-dimensional coordinates, flow velocities, and flow velocity directions of several points in the measured flow velocity data of several profiles, and obtains the unified plane flow velocity data of several profiles. Among them, the vertical mapping is:

[0056]

[0057] In the formula, Is the vertical mapping from the i-th point to the unified plane, x(u u , v i ) is the i-th point of the profile, y(u i , v i ) is, z(u i , v i ) is, u u Is the flow velocity of the i-th point in the measured flow velocity data, v i Is the flow velocity direction of the i-th point in the measured flow velocity data, u′ i Is the flow velocity of the i-th point in the unified plane flow velocity data, v′ i Is the flow velocity direction of the i-th point in the unified plane flow velocity data, and A, B, C, and D are the first, second, third, and fourth constants respectively.

[0058] S4: Perform blind area data prediction and data completion processing on the unified plane flow velocity data of several profiles to obtain the unified plane flow velocity data of several profiles after completion processing.

[0059] Since it is difficult to measure the data in the blind area of the sectional velocity measurement data of the river section measured by the acoustic Doppler current profiler, in this embodiment, the device obtains the blind area data prediction and data completion processing for the unified plane velocity data of several sections, and obtains the unified plane velocity data of several sections after the completion processing. Among them, the blind area data prediction methods include but are not limited to gray prediction models, statistical models, machine learning, etc.; the gray prediction models include but are not limited to first-order one-dimensional gray prediction models and rolling gray prediction models, etc.; the statistical prediction models include but are not limited to autoregressive models, moving average models, and autoregressive integrated moving average models, etc.; machine learning includes but is not limited to support vector machines, neural network models, deep learning models, etc.; the data completion processing methods include but are not limited to local mean, moving average, etc.

[0060] Please refer to Figure 5 , Figure 5 which is a schematic flow chart of S4 in the sectional flow rate obtaining method provided by an embodiment of the present application, including steps S41 to S43, specifically as follows:

[0061] S41: Extract data according to the unified plane velocity data of several sections to obtain the lower bottom elevation data, near-surface velocity data, and near-bottom velocity data of several sections.

[0062] In this embodiment, the device extracts data according to the unified plane velocity data of several sections to obtain the lower bottom elevation data, near-surface velocity data, and near-bottom velocity data of several sections. Among them, the lower bottom elevation data includes the elevation coordinates of several points at the lower bottom of the section.

[0063] S42: Input the lower bottom elevation data, near-surface velocity data, and near-bottom velocity data of several sections into the corresponding blind area data prediction models respectively for blind area data prediction, and obtain the lower bottom blind area elevation prediction data, near-surface blind area velocity prediction data, and near-bottom blind area velocity prediction data of several sections output by the corresponding blind area data prediction models.

[0064] In this embodiment, the device inputs the lower bottom elevation data, near-surface velocity data, and near-bottom velocity data of several sections into the corresponding blind area data prediction models respectively for blind area data prediction, and obtains the lower bottom blind area elevation prediction data, near-surface blind area velocity prediction data, and near-bottom blind area velocity prediction data of several sections output by the corresponding blind area data prediction models. Among them, the blind area data prediction model uses a long short-term memory neural network model, and the long short-term memory neural network model is as follows:

[0065]

[0066] In the formula, it is the vector output by the input gate corresponding to the t-th time step, x t is the input vector corresponding to the t-th time step, f t is the vector output by the forget gate corresponding to the t-th time step, o t is the vector output by the memory cell corresponding to the t-th time step, is the intermediate vector of the output gate corresponding to the t-th time step, c t is the vector output by the output gate corresponding to the t-th time step, W i 、W f 、W o and W c are the first, second, third, and fourth trainable weight matrices respectively, b i 、b f 、b o and b c are the first, second, third, and fourth bias vectors respectively, h t is the hidden layer state vector corresponding to the t-th time step, y t is the prediction vector corresponding to the t-th time step, that is, the prediction data output by the long short-term memory neural network model. σ() is the activation function, and ⊙ is the Hadamard product.

[0067] In this embodiment, the acquisition device respectively uses the lower bottom elevation data, near-surface flow velocity data, and near-bottom flow velocity data of several profiles as the training data of a preset long short-term memory neural network model, performs blind area data prediction and model training on the long short-term memory neural network model, obtains a lower bottom elevation prediction model and the lower bottom blind area elevation prediction data of several profiles output by the lower bottom elevation prediction model, obtains a near-surface flow velocity prediction model and the near-surface blind area flow velocity prediction data of several profiles output by the near-surface flow velocity prediction model, obtains a near-bottom flow velocity prediction model and the near-bottom blind area flow velocity prediction data of several profiles output by the near-bottom flow velocity prediction model,

[0068] In a feasible embodiment, the acquisition device is also used to receive the parameters of the prediction model input by the user. Among them, the parameters can include the prediction model type, learning step size, number of training times, learning rate, activation function, number of neuron layers and the number of neurons, etc.

[0069] In a feasible embodiment, for the lower bottom blind area elevation prediction data, the acquisition device is also used to receive the bank type parameters input by the user, that is, vertical bank and sloping bank. Among them, when selecting a vertical bank, the shore distance parameter also needs to be received.

[0070] S43: Based on the predicted elevation data of the lower bottom blind area, the predicted flow velocity data of the near-surface blind area, and the predicted flow velocity data of the near-bottom blind area for several profiles, perform data completion processing on the unified plane flow velocity data of the corresponding profiles to obtain the unified plane flow velocity data of several profiles after the completion processing.

[0071] In this embodiment, the acquisition device performs data completion processing on the unified plane flow velocity data of the corresponding profiles based on the predicted elevation data of the lower bottom blind area, the predicted flow velocity data of the near-surface blind area, and the predicted flow velocity data of the near-bottom blind area for several profiles, and obtains the unified plane flow velocity data of several profiles after the completion processing.

[0072] In a feasible embodiment, the acquisition device interpolates the missing values of the unified plane flow velocity data of several profiles after the completion processing.

[0073] In an alternative embodiment, it further includes step S6: screening the unified plane flow velocity data. Please refer to Figure 6 , Figure 6 which is a schematic flowchart of S6 in the profile flow rate acquisition method provided by another embodiment of the present application, including steps S61 to S62, specifically as follows:

[0074] S61: According to a preset unit range, construct a point set of several points in the unified plane flow velocity data, perform mean processing and standard deviation processing on the flow velocities of several points in the point set, and add the obtained mean and standard deviation to obtain the flow velocity threshold of several points.

[0075] In this embodiment, the acquisition device constructs a point set of several points in the unified plane flow velocity data according to a preset unit range, performs mean processing and standard deviation processing on the flow velocities of several points in the point set, and adds the obtained mean and standard deviation to obtain the flow velocity threshold of several points.

[0076] S62: According to the flow velocities of several points in the unified plane flow velocity data of several profiles after the completion processing and the corresponding flow velocity thresholds, perform screening processing on several points in the unified plane flow velocity data to obtain the unified plane flow velocity data of several profiles after the screening processing.

[0077] In this embodiment, the acquisition device, according to the flow velocities of several points in the unified plane flow velocity data of several profiles after the completion processing and the corresponding flow velocity thresholds, if the flow velocity is greater than the flow velocity threshold, discards the corresponding points as abnormal points, and performs screening processing on several points in the unified plane flow velocity data to obtain the unified plane flow velocity data of several profiles after the screening processing.

[0078] S5: Calculate the flow rate based on the unified planar flow velocity data of several profiles after completion processing to obtain the profile flow rate data of the cross-section of the river to be measured.

[0079] In this embodiment, the acquisition device calculates the flow rate based on the unified planar flow velocity data of several profiles after completion processing to obtain the profile flow rate data of the cross-section of the river to be measured. By performing unified planar flow velocity data conversion, blind area prediction, and data completion processing on the measured flow velocity data of multiple profiles, complete unified planar flow velocity data is obtained for flow rate calculation, improving the stability, accuracy, and reliability of the calculation of the profile flow rate data of the river cross-section.

[0080] Please refer to Figure 7 , Figure 7 which is a schematic flowchart of step S5 in the profile flow rate acquisition method provided by an embodiment of the present application, including step S51, specifically as follows:

[0081] S51: Obtain the areas of several points in the unified planar flow velocity data of several profiles after screening processing. According to the flow velocities, areas, and a preset flow rate calculation algorithm of several points in the unified planar flow velocity data of several profiles after screening processing, obtain the flow rates of several profiles. Perform averaging processing on the flow rates of several profiles to obtain the profile flow rate data of the cross-section of the river to be measured.

[0082] In this embodiment, the acquisition device obtains the areas of several points in the unified planar flow velocity data of several profiles after screening processing. Specifically, the acquisition device obtains the grid regions where several points are located and the lengths and widths of the grid regions according to the three-dimensional coordinates of several points in the unified planar flow velocity data, and performs area calculation based on the lengths and widths to obtain the areas of several points.

[0083] The acquisition device obtains the flow rates of several profiles according to the flow velocities, areas, and a preset flow rate calculation algorithm of several points in the unified planar flow velocity data of several profiles after screening processing, and performs averaging processing on the flow rates of several profiles to obtain the profile flow rate data of the cross-section of the river to be measured. Among them, the flow rate calculation algorithm is:

[0084]

[0085] In the formula, Q is the flow rate of the profile, s i is the flow velocity of several points in the unified planar flow velocity data of several profiles after screening processing, A i is the area of several points in the unified planar flow velocity data of several profiles after screening processing.

[0086] Please refer to Figure 8 , Figure 8Schematic structural diagram of a cross-sectional flow acquisition device provided by an embodiment of the present application. This device can implement all or part of the cross-sectional flow acquisition device through software, hardware, or a combination of both. The device 8 includes:

[0087] A data acquisition module 81, configured to obtain measurement flow velocity data of a plurality of cross-sections of a river to be measured. Among them, the measurement flow velocity data includes three-dimensional coordinates, flow velocity, and flow velocity direction of a plurality of points on the cross-section;

[0088] A unified plane construction module 82, configured to determine the center points of a plurality of cross-sections according to the three-dimensional coordinates of a plurality of points in the measurement flow velocity data of the plurality of cross-sections; construct a vertical plane of the flow velocity direction based on the center points of the plurality of cross-sections as the unified plane of the river cross-section to be measured;

[0089] A data mapping module 83, configured to perform a vertical mapping to the unified plane of the river cross-section to be measured according to the measurement flow velocity data of the plurality of cross-sections to obtain unified plane flow velocity data of the plurality of cross-sections;

[0090] A data completion module 84, configured to perform blind area data prediction and data completion processing on the unified plane flow velocity data of the plurality of cross-sections to obtain the unified plane flow velocity data of the plurality of cross-sections after the completion processing;

[0091] A cross-sectional flow calculation module 85, configured to calculate the flow rate according to the unified plane flow velocity data of the plurality of cross-sections after the completion processing to obtain the cross-sectional flow rate data of the river cross-section to be measured.

[0092] In the embodiment of the present application, through a data acquisition module, measurement flow velocity data of a plurality of profiles of a river section to be measured is obtained, where the measurement flow velocity data includes three-dimensional coordinates, flow velocity, and flow velocity direction of a plurality of points on the profile; through a unified plane construction module, according to the three-dimensional coordinates of a plurality of points in the measurement flow velocity data of a plurality of profiles, the center points of the plurality of profiles are determined; according to the center points of the plurality of profiles, a vertical plane of the flow velocity direction is constructed as the unified plane of the river section to be measured; through a data mapping module, according to the measurement flow velocity data of a plurality of profiles, a perpendicular mapping is made to the unified plane of the river section to be measured to obtain unified plane flow velocity data of the plurality of profiles; through a data completion module, blind area data prediction and data completion processing are performed on the unified plane flow velocity data of the plurality of profiles to obtain the unified plane flow velocity data of the plurality of profiles after the completion processing; through a profile flow rate calculation module, flow rate calculation is performed according to the unified plane flow velocity data of the plurality of profiles after the completion processing to obtain profile flow rate data of the river section to be measured. By performing unified plane flow velocity data conversion, blind area prediction, and data completion processing on the measurement flow velocity data of multiple profiles, complete unified plane flow velocity data is obtained for flow rate calculation, improving the stability, accuracy, and reliability of the calculation of the profile flow rate data of the river section.

[0093] Please refer to Figure 9 , Figure 9 which is a schematic structural diagram of a computer device provided by an embodiment of the present application. The computer device 9 includes: a processor 91, a memory 92, and a computer program 93 stored on the memory 92 and executable on the processor 91; the computer device can store multiple instructions, and the instructions are suitable for being loaded and executed by the processor 91 to perform the above Figures 1 to 7 method steps shown, and the specific execution process can refer to the specific description shown in Figures 1 to 7 and will not be elaborated here.

[0094] Among them, the processor 91 may include one or more processing cores. The processor 91 uses various interfaces and lines to connect various parts within the server. By running or executing instructions, programs, code sets, or instruction sets stored in the memory 92, and by calling the data in the memory 92, it executes various functions of the profile traffic acquisition device 8 and processes data. Optionally, the processor 91 may be implemented in at least one hardware form of digital signal processing (DSP), field-programmable gate array (FPGA), or programmable logic array (PLA). The processor 91 may integrate one or a combination of a central processing unit (CPU), a graphics processing unit (GPU), and a modem, etc. Among them, the CPU mainly processes the operating system, user interface, application programs, etc.; the GPU is responsible for rendering and drawing the content to be displayed on the touch display screen; the modem is used to process wireless communication. It can be understood that the above-mentioned modem may not be integrated into the processor 91 and may be implemented separately by a single chip.

[0095] Among them, the memory 92 may include a random access memory (RAM) and may also include a read-only memory. Optionally, the memory 92 includes a non-transitory computer-readable storage medium. The memory 92 can be used to store instructions, programs, code, code sets, or instruction sets. The memory 92 may include a program storage area and a data storage area. Among them, the program storage area may store instructions for implementing the operating system, instructions for at least one function (such as touch instructions, etc.), instructions for implementing the above-mentioned various method embodiments, etc.; the data storage area may store the data involved in the above-mentioned various method embodiments. Optionally, the memory 92 may also be at least one storage device located far from the aforementioned processor 91.

[0096] The embodiment of the present application also provides a storage medium, which can store multiple instructions, and the instructions are suitable for being loaded and executed by the processor to perform the above Figures 1 to 7 shown method steps, and the specific execution process can be referred to Figures 1 to 7 the specific description shown, and details are not described herein.

[0097] Those skilled in the art can clearly understand that, for the convenience and conciseness of description, only the above-mentioned division of each functional unit and module is used as an example. In actual applications, the above-mentioned functions can be assigned to different functional units and modules according to needs, that is, the internal structure of the device is divided into different functional units or modules to complete all or part of the functions described above. Each functional unit and module in the embodiments can be integrated into a processing unit, or each unit can exist physically alone, or two or more units can be integrated into one unit. The above-mentioned integrated unit can be implemented in the form of hardware or in the form of a software functional unit. In addition, the specific names of each functional unit and module are only for the convenience of mutual distinction and do not limit the protection scope of this application. The specific working processes of the units and modules in the above system can refer to the corresponding processes in the foregoing method embodiments and will not be elaborated herein.

[0098] In the above embodiments, the descriptions of the various embodiments have their own emphases. For the parts not detailed or recorded in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0099] Those of ordinary skill in the art can realize that the units and algorithm steps of each example described in combination with the embodiments disclosed herein can be implemented by electronic hardware, or by a combination of computer software and electronic hardware. Whether these functions are executed in a hardware or software manner depends on the specific application and design constraints of the technical solution. Professional technicians can use different methods to implement the described functions for each specific application, but such implementation should not be considered to exceed the scope of the present invention.

[0100] In the embodiments provided by the present invention, it should be understood that the disclosed device / terminal device and method can be implemented in other ways. For example, the device / terminal device embodiments described above are only illustrative. For example, the division of the module or unit is only a logical function division. In actual implementation, there may be other division methods. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the displayed or discussed coupling or direct coupling or communication connection to each other can be through some interfaces. The indirect coupling or communication connection of the device or unit can be in an electrical, mechanical or other form.

[0101] The unit described as a separated component may or may not be physically separated, and the component displayed as a unit may or may not be a physical unit, that is, it may be located in one place, or may be distributed to multiple network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0102] In addition, in each embodiment of the present invention, each functional unit can be integrated into one processing unit, or each unit can exist physically alone, or two or more units can be integrated into one unit. The above-mentioned integrated unit can be implemented in the form of hardware or in the form of a software functional unit.

[0103] If the integrated module / unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, to implement all or part of the processes in the above-mentioned embodiment methods of the present invention, it can also be completed by instructing relevant hardware through a computer program. The computer program can be stored in a computer-readable storage medium. When the computer program is executed by a processor, the steps of the above-mentioned various method embodiments can be implemented. Among them, the computer program includes computer program code, and the computer program code can be in the form of source code, object code, executable file or some intermediate form, etc.

[0104] The present invention is not limited to the above-mentioned embodiments. If various changes or deformations to the present invention do not deviate from the spirit and scope of the present invention, and if these changes and deformations fall within the scope of the claims of the present invention and equivalent technical scope, then the present invention also intends to include these changes and deformations.

Claims

1. A method for obtaining a profile flow, characterized in that: The following steps are involved: Obtaining measured flow velocity data of a plurality of cross sections of the river section to be measured, wherein the measured flow velocity data includes three-dimensional coordinates, flow velocity and flow velocity direction of a plurality of points on the cross section; Determine the center points of several sections according to the three-dimensional coordinates of several points in the measured flow velocity data of several sections; construct a vertical plane of the flow velocity direction according to the center points of several sections as a unified plane of the river section to be measured; According to the measured flow velocity data of the plurality of sections, vertical mapping is performed to a unified plane of the cross section of the river to be measured to obtain unified plane flow velocity data of the plurality of sections; Performing blind area data prediction and data completion processing on the unified plane flow velocity data of the plurality of sections to obtain the unified plane flow velocity data of the plurality of sections after completion processing; The flow rate is calculated based on the unified plane flow velocity data of several sections after completion processing to obtain the profile flow data of the river section to be measured.

2. The method for obtaining the profile flow according to claim 1, characterized in that: The three-dimensional coordinates include horizontal coordinates, vertical coordinates and elevation coordinates; The method of determining the center points of the plurality of sections according to the three-dimensional coordinates of the plurality of points in the measured flow velocity data of the plurality of sections comprises the steps of: According to the three-dimensional coordinates of several points in the measured flow velocity data of several sections and a preset three-dimensional surface geometric center distance calculation algorithm, the three-dimensional surface geometric center distance of several points of the several sections is obtained, wherein the three-dimensional surface geometric center distance calculation algorithm is: In the formula, is the average horizontal coordinate, N is the total number of points in the profile, x i is the horizontal coordinate of the i-th point, is the average vertical coordinate, y i is the vertical coordinate of the ith point, is the average elevation coordinate, z i is the elevation coordinate of the i-th point, d(x i,i,i ) is the geometric center distance of the three-dimensional surface of the i-th point; According to the three-dimensional surface geometric center distances of several points of the same section, the point with the smallest three-dimensional surface geometric center distance is taken as the center point of the corresponding section to obtain the center points of several sections.

3. The method for obtaining the profile flow according to claim 2, characterized in that: The method of constructing a vertical plane in the flow velocity direction according to the center points of a plurality of cross sections comprises the steps of: The average flow velocity direction of the unit range area of ​​the center points of the several sections is obtained, and the vertical plane of the flow velocity direction is constructed according to the three-dimensional coordinates of the center points of the several sections and the average flow velocity direction of the unit range area.

4. The method for obtaining the profile flow rate according to claim 3, characterized in that: The method of mapping the measured flow velocity data of the plurality of sections vertically to the unified plane of the river section to be measured to obtain the unified plane flow velocity data of the plurality of sections comprises the steps of: A three-dimensional curved surface vertical mapping method is adopted to construct a vertical mapping of several points of several sections to the unified plane according to the three-dimensional coordinates, flow velocity and flow velocity direction of several points in the measured flow velocity data of several sections, and obtain the unified plane flow velocity data of several sections, wherein the vertical mapping is: In the formula, is the vertical mapping of the ith point to the uniform plane, x(u i,i ) is the i-th point of the profile, y(u i,i ) is, z(u i,i ) is, u i is the velocity of the ith point in the measured velocity data, v i is the velocity direction of the i-th point in the measured velocity data, u′ i is the velocity of the ith point in the uniform plane velocity data, v′ i is the velocity direction of the ith point in the uniform plane velocity data, and A, B, C, and D are the first, second, third, and fourth constants, respectively.

5. The method for obtaining cross-sectional flow according to claim 4, characterized in that: The method of performing blind area data prediction and data completion processing on the unified plane velocity data of a plurality of sections to obtain the unified plane velocity data of the plurality of sections after completion processing comprises the steps of: Extracting data based on the unified plane velocity data of the plurality of sections to obtain lower bottom elevation data, near-surface velocity data, and near-bottom surface velocity data of the plurality of sections, wherein the lower bottom elevation data includes the elevation coordinates of a plurality of points of the lower bottom of the section; Inputting lower bottom elevation data, near-surface velocity data, and near-bottom surface velocity data of several sections into corresponding blind spot data prediction models to perform blind spot data prediction, and obtaining lower bottom blind spot elevation prediction data, near-surface blind spot velocity prediction data, and near-bottom surface blind spot velocity prediction data of several sections output by corresponding blind spot data prediction models; According to the lower bottom blind spot elevation prediction data, near surface blind spot flow velocity prediction data and near bottom blind spot flow velocity prediction data of several sections, the unified plane flow velocity data of the corresponding sections are completed to obtain the unified plane flow velocity data of several sections after completion.

6. The method for obtaining cross-sectional flow according to claim 5, characterized in that: Before the flow calculation is performed based on the unified plane flow velocity data of the multiple sections after the completion process to obtain the section flow data of the river section to be measured, the method further includes the steps of: screening the unified plane flow velocity data; The screening of the uniform plane flow velocity data comprises the steps of: According to a preset unit range, a point set of several points in the unified plane flow velocity data is constructed, mean processing and standard deviation processing are performed according to the flow velocities of several points in the point set, and the obtained mean and standard deviation are added to obtain flow velocity thresholds of the several points; According to the flow velocities of several points in the unified plane flow velocity data of several sections after completion processing and the corresponding flow velocity threshold, several points in the unified plane flow velocity data are screened to obtain the unified plane flow velocity data of several sections after screening processing.

7. The method for obtaining the cross-sectional flow rate according to claim 6, characterized in that: The flow calculation is performed according to the unified plane flow velocity data of the multiple sections after the completion processing to obtain the cross-sectional flow data of the river section to be measured, including the steps of: The areas of several points in the unified plane velocity data of several sections after screening are obtained, and the flow rates of several sections are obtained according to the flow rates and areas of several points in the unified plane velocity data of several sections after screening and a preset flow calculation algorithm. The flow rates of several sections are averaged to obtain the cross-sectional flow data of the river section to be measured, wherein the flow calculation algorithm is: Where Q is the flow rate of the section, s i To screen the velocity of several points in the unified plane velocity data of several sections after processing, A i It is the area of ​​several points in the unified plane velocity data of several sections after screening.

8. A profile flow acquisition device, characterized in that: include: A data acquisition module, used to obtain measured flow velocity data of several sections of the river section to be measured, wherein the measured flow velocity data includes three-dimensional coordinates, flow velocity and flow velocity direction of several points on the section; A unified plane construction module is used to determine the center points of several sections according to the three-dimensional coordinates of several points in the measured flow velocity data of several sections; and to construct a vertical plane in the flow velocity direction according to the center points of several sections as a unified plane of the river section to be measured; A data mapping module is used to perform vertical mapping to a unified plane of the river section to be measured based on the measured flow velocity data of the plurality of sections, so as to obtain unified plane flow velocity data of the plurality of sections; A data completion module, used for performing blind area data prediction and data completion processing on the unified plane flow velocity data of several sections, and obtaining the unified plane flow velocity data of several sections after completion processing; The profile flow calculation module is used to calculate the flow according to the unified plane velocity data of several profiles after completion processing, and obtain the profile flow data of the river section to be measured.

9. A computer device, characterized in that: include: A processor, a memory, and a computer program stored in the memory and executable on the processor; when the computer program is executed by the processor, the steps of the profile flow acquisition method according to any one of claims 1 to 7 are implemented.

10. A storage medium, characterized in that: The storage medium stores a computer program, and when the computer program is executed by a processor, the steps of the profile flow acquisition method according to any one of claims 1 to 7 are implemented.

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