Channel measurement method and device, terminal equipment and storage medium

Abstract

The invention provides a channel measurement method and device, terminal equipment and a storage medium, and is suitable for the technical field of measurement, and the method comprises the steps: carrying out the time-space synchronization processing of channel magnetic field signal information, channel positioning information and preset channel measurement path information, and generating channel magnetic field positioning information; analyzing and processing the channel magnetic field positioning information to obtain channel terrain identification information and initial channel dam leakage identification information; performing optimization processing on the initial channel dam leakage identification information to obtain target channel dam leakage identification information; and generating channel measurement information according to the target channel dam leakage identification information and the channel terrain identification information. According to the invention, non-contact leakage monitoring of the channel dam is realized, the channel detection efficiency and the positioning precision are improved, and accurate and comprehensive channel measurement information and dam leakage conditions are provided for safety monitoring of water conservancy projects.

Description

Technical Field

[0001] This application belongs to the field of measurement technology, and in particular relates to waterway measurement methods, devices and terminal equipment. Background Technology

[0002] In the field of waterway surveying, with the rapid development of water conservancy projects and the increasing requirements for safe operation of waterways, waterway surveying technology is developing towards intelligence, efficiency, and integration.

[0003] Currently, waterway surveying primarily employs a combination of unmanned survey vessel platforms and sensor technologies. These unmanned survey vessels are equipped with devices such as sonar systems and multibeam echo sounders. Utilizing multibeam synchronous transmission technology, they can achieve rapid, full-area coverage in deep water regions, generating high-precision three-dimensional riverbed models and providing efficient data support for waterway maintenance.

[0004] However, in existing technologies, satellite positioning signals are easily interfered with in waterway areas with complex weather or special geographical environments, such as narrow inland waterways during heavy rain or dense fog, leading to a decrease in the accuracy of waterway positioning information. Underwater topographic surveying is limited by equipment performance, and in shallow water areas or areas with dense reefs, the magnetic field signal information obtained by sonar systems deviates from the actual topography, thereby reducing the comprehensiveness and accuracy of waterway surveying and failing to provide a sufficiently reliable basis for waterway management and maintenance. Summary of the Invention

[0005] In view of this, embodiments of this application provide a waterway measurement method, apparatus, terminal equipment, and storage medium, aiming to solve the problems in the prior art where waterway positioning information is easily interfered with, magnetic field signals deviate from actual terrain, and the comprehensiveness and accuracy of waterway measurement cannot be guaranteed.

[0006] The first aspect of this application provides a waterway surveying method, including: Acquire channel magnetic field signal information and channel positioning information; The channel magnetic field signal information, channel positioning information, and preset channel measurement path information are processed in a time-space synchronization manner to generate channel magnetic field positioning information. The channel magnetic field positioning information is analyzed and processed to obtain channel topography identification information and initial channel dam leakage identification information; The initial channel dam leakage identification information is optimized to obtain the target channel dam leakage identification information; Based on the target waterway dam seepage identification information and waterway topography identification information, waterway measurement information is generated.

[0007] A second aspect of this application provides a waterway surveying apparatus, comprising: The information acquisition module is used to acquire channel magnetic field signal information and channel positioning information; The channel magnetic field positioning information generation module is used to perform spatiotemporal synchronization processing on the channel magnetic field signal information, channel positioning information and preset channel measurement path information to generate channel magnetic field positioning information. The channel topography identification information and initial channel dam leakage identification information generation module is used to analyze and process the channel magnetic field positioning information to obtain channel topography identification information and initial channel dam leakage identification information. The target channel dam seepage identification information generation module is used to optimize the initial channel dam seepage identification information to obtain the target channel dam seepage identification information. The waterway measurement information generation module is used to generate waterway measurement information based on the target waterway dam seepage identification information and waterway topography identification information.

[0008] A third aspect of this application provides a terminal device, which includes a memory and a processor. The memory stores a computer program that can run on the processor. When the processor executes the computer program, it implements the steps of the waterway measurement method described in the first aspect above.

[0009] A fourth aspect of this application provides a computer-readable storage medium, comprising: storing a computer program, which, when executed by a processor, implements the steps of the waterway measurement method as described in the first aspect above.

[0010] Compared with the prior art, the beneficial effects of the embodiments of this application are: effectively solving the problems of low efficiency, poor accuracy, and difficulty in locating three-dimensional channels in the prior art, improving the accuracy of waterway terrain identification and the efficiency of dam seepage detection, realizing non-contact quantitative detection of seepage, improving the adaptability of waterway measurement in complex water conservancy environments, and thus providing efficient and accurate technical support for the safety monitoring of water conservancy projects. Attached Figure Description

[0011] To more clearly illustrate the technical solutions in the embodiments of this application, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0012] Figure 1 This is a schematic diagram illustrating the implementation process of the waterway surveying method provided in Embodiment 1 of this application; Figure 2 This is a schematic diagram illustrating the implementation process of the waterway surveying method provided in Embodiment 2 of this application; Figure 3 This is a schematic diagram illustrating the implementation process of the waterway surveying method provided in Embodiment 3 of this application; Figure 4 This is a schematic diagram illustrating the implementation process of the waterway surveying method provided in Embodiment 4 of this application; Figure 5 This is a schematic diagram illustrating the implementation process of the waterway surveying method provided in Embodiment 5 of this application; Figure 6 This is a schematic diagram illustrating the implementation process of the waterway surveying method provided in Embodiment Six of this application; Figure 7 This is a schematic diagram illustrating the implementation process of the waterway surveying method provided in Embodiment 7 of this application; Figure 8 This is a schematic diagram of the structure of the waterway measurement device provided in the embodiments of this application; Figure 9 This is a schematic diagram of the terminal device provided in the embodiments of this application. Detailed Implementation

[0013] In the following description, specific details such as particular system architectures and techniques are set forth for illustrative purposes and not for limitation, in order to provide a thorough understanding of the embodiments of this application. However, those skilled in the art will understand that this application may also be implemented in other embodiments without these specific details. In other instances, detailed descriptions of well-known systems, apparatuses, circuits, and methods have been omitted so as not to obscure the description of this application with unnecessary detail.

[0014] To illustrate the technical solution described in this application, specific embodiments are provided below.

[0015] Figure 1 A flowchart illustrating the implementation of the waterway surveying method provided in Embodiment 1 of this application is shown, and detailed below: Step S101: Obtain channel magnetic field signal information and channel positioning information.

[0016] In this embodiment, the channel magnetic field signal information refers to the alternating magnetic field strength data detected by the UAV in the channel and dam area. It can include the three-dimensional components and frequency characteristics of the magnetic field, and can be used to reflect the distribution of the current field below the channel and dam. Since the current field and seepage field are coupled, the current distribution of the dam seepage channel can be inverted through the magnetic field signal. The three-dimensional components of the magnetic field can be the spatial distribution characteristics of the magnetic field, and the frequency characteristics can be components consistent with the transmission frequency of the UAV's power supply system. The channel magnetic field signal information can be generated by inducing an electromotive force in the alternating current field through an array of 8-24 receiving coils inside the spherical sensor housing. After processing by a resonant matching circuit and signal processing module, it is converted into digital magnetic field strength data, which is then collected by a hexacopter UAV platform along a preset "S"-shaped route (altitude 10-50m, speed 2-5m / s) and transmitted back in real time via a 4G / 5G module. The diameter of the spherical sensor housing can be 10-30cm, the number of turns in a single coil of the receiving coil array can be 100-500, the resonant matching circuit can be matched with the transmission frequency, and the signal processing module can include a narrowband amplifier with a gain of 60-80dB. Channel positioning information refers to the spatial coordinate data collected by the UAV when acquiring magnetic field signals. This data is used to bind the magnetic field signals to the physical locations of waterways and embankments, ensuring that magnetic field anomalies correspond to specific waterway sections or embankment locations. It is the core data for achieving the association between "magnetic field signal and spatial location," and can be acquired by integrating RTK-GPS and inertial navigation units within the spherical sensor housing. The positioning accuracy can reach ±1cm. Channel positioning information can be acquired synchronously with channel magnetic field signal information. Through timestamp alignment, each set of channel magnetic field signal information can be matched with corresponding three-dimensional coordinates (longitude, latitude, and elevation). It can also be transmitted back along with the channel magnetic field signal information via the UAV's 4G / 5G module for subsequent spatiotemporal synchronization processing.

[0017] Step S102: Perform spatiotemporal synchronization processing on the channel magnetic field signal information, channel positioning information, and preset channel measurement path information to generate channel magnetic field positioning information.

[0018] In this embodiment, the preset waterway measurement path information can be manually set, which can refer to the flight route parameters planned by the UAV before performing the waterway measurement task, including the starting point, ending point, turning point, flight altitude, speed and path shape, etc. It can adopt an "S" shaped path according to the dam axis, the flight altitude can be adjusted within the range of 10-50m, and the speed can be set to 2-5m / s to ensure that the waterway and dam area can be fully covered, so that the UAV can take into account both the measurement range and the data accuracy when collecting magnetic field signals and positioning information. The process can begin by extracting the timestamps of the channel magnetic field signal and the channel positioning information. Using the timestamp of the magnetic field signal as a benchmark, the time deviation between the two is calculated by finding and matching the corresponding timestamp of the positioning information. Abnormal data with deviations exceeding a threshold are eliminated to ensure temporal consistency. Then, the channel positioning information and the preset channel measurement path information are converted to the same local coordinate system. Using the preset channel measurement path as a benchmark, the data is divided by segment, and the distance from each magnetic field signal sampling point to each segment is calculated. The sampling points are assigned to the nearest segment to achieve spatial association between the magnetic field signal and the aerial survey path. Then, the magnetic field signals assigned to the same segment are sorted by the mileage along the segment to form continuous distributed data. Finally, the time-synchronized magnetic field signal information is bound with the corresponding spatial location channel positioning information and segment information to generate channel magnetic field positioning information containing magnetic field strength, three-dimensional coordinates, and the segment to which it belongs.

[0019] Step S103: The channel magnetic field positioning information is analyzed and processed to obtain channel topography identification information and initial channel dam leakage identification information.

[0020] In this embodiment, spatial coordinate data related to the waterway topography can be extracted from the waterway magnetic field positioning information based on the preset waterway measurement path information. Combined with the elevation information obtained by UAV aerial survey, waterway topography identification information is generated through 3D modeling to reflect the waterway's water depth, shoreline, and dam surface elevation and other topographic features. At the same time, based on the mathematical isomorphism of Darcy's law and Ohm's law, multi-coil signal synthesis and frequency domain analysis are performed on the magnetic field strength data in the waterway magnetic field positioning information to extract leakage-related features such as magnetic field amplitude anomalies and frequency response characteristics. Then, the Biot-Savart law can be used to invert the current density distribution to identify these features, screen out anomalies that meet the leakage characteristics, form initial waterway dam leakage identification information, and mark the spatial location of suspected leakage.

[0021] Step S104: Optimize the initial channel dam leakage identification information to obtain the target channel dam leakage identification information.

[0022] In this embodiment, the coordinates of initially identified suspected seepage points can be used as a basis, combined with preset physical boundary conditions of the dam, to determine the optimized search range, ensuring that all candidate points are within the actual dam structure. Then, an objective function is constructed, using the error between the measured magnetic field data collected by the UAV and the magnetic field data calculated based on a current field simulation model as the optimization objective. The simulation model can be based on the Biot-Savart law, calculating the theoretical magnetic field distribution through the assumed equivalent current of the seepage channel. Multiple candidate seepage point coordinates are then randomly generated as an initial population, with each candidate point corresponding to a set of equivalent current values. For each candidate point, the fitness of that candidate point can be calculated according to the objective function. The smaller the fitness value, the better the magnetic field distribution of the candidate point matches the measured data. This allows for the simulation to be more effective. The pseudo-group optimization behavior updates the candidate point positions. By learning the position information of the current best candidate point and introducing random perturbations, the candidate point gradually moves towards the region with smaller errors. This process is repeated to iteratively update the candidate points and their fitness until the number of iterations reaches a preset value or the error is less than a set threshold. The coordinates of the best candidate point obtained at this time are the precise location of the seepage channel. At the same time, the seepage flow can be calculated based on the equivalent current value corresponding to the optimal position and the empirical coefficient determined by the calibration experiment. Then, the optimized three-dimensional coordinates of the seepage channel, the equivalent current value, and the seepage flow can be integrated to form the seepage identification information of the target waterway dam. This information satisfies the similarity principle between the current field and the seepage field and conforms to the physical constraints of the dam structure, ensuring the accuracy and reliability of waterway dam seepage identification. The preset physical boundary conditions of the dam refer to the geometric and physical constraints that limit the spatial distribution of seepage channels. These are a prerequisite for ensuring that the seepage detection results conform to the actual engineering scenario. They can include: geometric boundaries, i.e., spatial limitations of the dam, such as dam crest elevation, dam base elevation, dam width, and dam axis orientation, which can be used to define the three-dimensional spatial region where seepage channels may exist; and physical characteristic boundaries, i.e., constraints on the current field and seepage field based on the principle of hydroelectric analogy, such as insulation boundaries and equipotential boundaries, which can be used to ensure that the inverted current distribution conforms to the actual seepage law. The preset physical boundary conditions of the dam can be artificially set based on the geometric boundaries of the dam, or they can be artificially set based on the physical characteristic boundaries of the dam.

[0023] Step S105: Generate waterway measurement information based on the target waterway dam leakage identification information and waterway topography identification information.

[0024] In this embodiment, the three-dimensional coordinates and seepage flow rate of the seepage channel included in the target waterway dam seepage identification information can be spatially correlated with the waterway topography features such as waterway depth, shoreline, and dam surface elevation in the waterway topography identification information. The seepage point is then accurately projected onto the three-dimensional coordinate system of the waterway topography. Based on the principle of hydroelectric analogy and the spatial correspondence between the two, the impact range of the seepage channel on the waterway topography can be analyzed. For example, the seepage flow rate can be used to determine whether the seepage has caused local waterway scouring or dam slope deformation. Then, all the correlated data can be integrated, and the basic parameters of the waterway topography can be merged with the specific information of the seepage hazard to form waterway measurement information that includes the overall waterway topography and the location and degree of dam seepage. This information not only reflects the topographic features of the waterway but also clearly marks the seepage hazard, providing a comprehensive basis for waterway safety assessment and maintenance.

[0025] The waterway measurement method provided in this application effectively solves the problems of low efficiency, poor accuracy, and difficulty in locating three-dimensional channels in the prior art, improves the accuracy of waterway terrain identification and the efficiency of dam seepage detection, realizes non-contact quantitative seepage detection, and improves the adaptability of waterway measurement in complex water conservancy environments, thereby providing efficient and accurate technical support for the safety monitoring of water conservancy projects.

[0026] Figure 2 The flowchart illustrating the implementation of the waterway surveying method provided in Embodiment 2 of this application is shown. The difference between this method and Embodiment 1 is that step S102 specifically includes: Step S201: Extract time information from the channel magnetic field signal information and channel positioning information to generate multiple channel magnetic field signal time information and multiple channel positioning time information; the channel magnetic field signal time information and the channel positioning time information correspond one-to-one.

[0027] In this embodiment, the timestamp corresponding to each magnetic field sampling point can be extracted from the channel magnetic field signal information transmitted back by the UAV as the channel magnetic field signal time information; at the same time, the RTK-GPS timestamp corresponding to the magnetic field sampling point can be extracted from the channel positioning information as the channel positioning time information, so as to ensure that each set of channel magnetic field signal information can find matching channel positioning time information.

[0028] Step S202: Calculate the difference between the time information of the multiple channel magnetic field signals and the time information of the multiple channel positioning to obtain the time difference information of the multiple channel magnetic field positioning.

[0029] In this embodiment, a numerical difference calculation is performed on the one-to-one correspondence of the channel magnetic field signal time information and the channel positioning time information. That is, each channel magnetic field signal time information is subtracted from the corresponding channel positioning time information, and the absolute value obtained is the channel magnetic field positioning time difference information, which can be used to quantify the time synchronization deviation between the two.

[0030] Step S203: Determine whether the channel magnetic field positioning time difference information is greater than the preset channel magnetic field positioning time difference threshold; if yes, proceed to step S204; if no, proceed to step S205.

[0031] In this embodiment, the preset channel magnetic field positioning time difference threshold can be set manually, based on the UAV data transmission delay characteristics, and can be set to 10ms. By comparing each channel magnetic field positioning time difference with this threshold, data that meets the time synchronization standard can be filtered out.

[0032] Step S204: Delete the channel magnetic field signal time information and channel positioning time information corresponding to the channel magnetic field positioning time difference information.

[0033] In this embodiment, when the channel magnetic field positioning time difference information is greater than a preset threshold, it indicates that there is a time misalignment between the corresponding channel magnetic field signal information and the channel positioning information, which may lead to a mismatch between the magnetic field signal and the spatial position. Therefore, this time information and the corresponding channel magnetic field signal information and channel positioning information are deleted to avoid affecting the accuracy of subsequent processing.

[0034] Step S205: Based on the channel magnetic field signal time information and channel positioning time information corresponding to the channel magnetic field positioning time difference information, generate channel magnetic field signal effective time information and channel positioning effective time information.

[0035] In this embodiment, time information for which the channel magnetic field positioning time difference is not greater than a preset threshold is marked as valid. The corresponding channel magnetic field signal time information is the channel magnetic field signal valid time information, and the channel positioning time information is the channel positioning valid time information, ensuring that the time information processed subsequently meets the synchronization requirements.

[0036] Step S206: Perform spatiotemporal synchronization processing based on the channel magnetic field signal information corresponding to the channel magnetic field signal effective time information, the channel positioning information corresponding to the channel positioning effective time information, and the preset channel measurement path information to generate channel magnetic field positioning information.

[0037] In this embodiment, the channel magnetic field signal information corresponding to the effective time information of the channel magnetic field signal and the channel positioning information corresponding to the effective time information of the channel positioning can be bound by timestamp. Then, combined with the preset channel measurement path information, the channel positioning information is converted to a local coordinate system consistent with the preset path. The magnetic field signal is divided and matched according to the channel segment to form channel magnetic field positioning information containing magnetic field strength, three-dimensional coordinates, the channel segment to which it belongs and the effective timestamp, so as to achieve precise correlation between time and space.

[0038] The waterway measurement method provided in this application accurately extracts and matches time information, ensuring that each set of waterway magnetic field signal information has corresponding waterway positioning time information. By comparing the calculated waterway magnetic field positioning time difference information with a preset waterway magnetic field positioning time difference threshold, the time synchronization deviation is quantified, and misaligned information caused by transmission delays is eliminated. This avoids invalid data with inconsistent time causing negative interference to the subsequent data processing process. Furthermore, based on the valid time information, the magnetic field, positioning, and path information are associated, making the generated waterway magnetic field positioning information highly consistent in time and space. This provides a more reliable data foundation for subsequent analysis and processing, improves the accuracy of waterway measurement, and meets the demand for accurate data in water conservancy project safety monitoring.

[0039] Figure 3 The flowchart illustrating the implementation of the waterway surveying method provided in Embodiment 3 of this application is shown. Its difference from Embodiment 2 described above lies in: The preset waterway survey path information includes multiple preset waterway survey sub-path information; Step S206 specifically includes: Step S301: Perform time alignment processing on the channel magnetic field signal information corresponding to the channel magnetic field signal effective time information and the channel positioning information corresponding to the channel positioning effective time information to obtain channel magnetic field signal time alignment information and channel positioning time alignment information; the channel magnetic field signal time alignment information and the channel positioning time alignment information correspond one-to-one.

[0040] In this embodiment, the effective time information of the channel magnetic field signal can be used as a reference to interpolate and adjust the effective time information of the channel positioning so that the two are completely matched in the time dimension. This ensures that each channel magnetic field signal time alignment information has a corresponding channel positioning time alignment information, eliminates minor time deviations, and lays the time foundation for subsequent spatial correlation.

[0041] Step S302: Calculate the distance between the channel positioning time alignment information and multiple preset channel measurement sub-path information to obtain multiple channel measurement sub-path attribution determination distance information.

[0042] In this embodiment, the multiple preset waterway measurement sub-path information can all be manually set. The spatial distance between the three-dimensional coordinates corresponding to the waterway positioning time alignment information and the points on each preset waterway measurement sub-path information can be calculated. The distance to the positioning point on each sub-path is taken as the waterway measurement sub-path attribution determination distance information corresponding to that sub-path, quantifying the spatial correlation between the positioning point and each sub-path.

[0043] Step S303: Determine whether the minimum value of the multiple waterway measurement sub-path attribution determination distance information is less than the preset waterway measurement sub-path attribution determination distance threshold; if yes, proceed to step S304; if no, proceed to step S305.

[0044] In this embodiment, the preset distance threshold for determining the sub-path of the waterway measurement can be set manually or based on the accuracy settings of UAV aerial surveying. When the minimum value of the distance information for determining the sub-path of the waterway measurement is less than the preset distance threshold, it indicates that the spatial deviation between the positioning point and the corresponding sub-path is within the allowable range, and it can be directly assigned; otherwise, compensation processing of the waterway magnetic field signal is required.

[0045] Step S304: Generate channel magnetic field positioning information based on the channel magnetic field signal time alignment information corresponding to the minimum value of the multiple channel measurement sub-path attribution determination distance information, the channel measurement sub-path information corresponding to the minimum value of the multiple channel measurement sub-path attribution determination distance information, and the channel magnetic field signal time alignment information corresponding to the minimum value of the multiple channel measurement sub-path attribution determination distance information, etc.

[0046] In this embodiment, the time alignment information of the channel magnetic field signal corresponding to the minimum value of the channel measurement sub-path attribution determination distance information, the channel measurement sub-path information and its corresponding channel positioning time alignment information are bound together to clarify which sub-path the magnetic field signal belongs to, forming channel magnetic field positioning information containing sub-path identifiers, thereby achieving accurate association between magnetic field signals and sub-paths.

[0047] Step S305: Calculate the difference between the minimum value of the waterway measurement sub-path attribution determination distance information and the preset waterway measurement sub-path attribution determination distance threshold to obtain the magnetic field signal to be compensated waterway positioning distance difference information.

[0048] In this embodiment, the absolute value of the difference between the minimum value of the waterway measurement sub-path attribution determination distance information and the preset waterway measurement sub-path attribution determination distance threshold is calculated and used as the waterway positioning distance difference information to be compensated for magnetic field signals. This information reflects the degree of deviation between the positioning point and the sub-path, providing a quantitative basis for subsequent magnetic field signal compensation.

[0049] Step S306: The channel positioning time alignment information corresponding to the minimum value of the multiple channel measurement sub-path attribution determination distance information is used as the channel positioning information of the magnetic field signal to be compensated.

[0050] In this embodiment, the channel positioning time alignment information corresponding to the minimum value is determined as the positioning information that needs to be compensated, and the spatial position data to be processed is clearly defined as the channel positioning information of the magnetic field signal to be compensated.

[0051] Step S307: Use the time alignment information of the channel magnetic field signal corresponding to the channel positioning information of the magnetic field signal to be compensated as the channel magnetic field signal to be compensated.

[0052] In this embodiment, the corresponding channel magnetic field signal time alignment information can be found based on the channel positioning information of the magnetic field signal to be compensated, and it can be identified as the channel magnetic field signal to be compensated, ensuring that the compensation object corresponds to the positioning information.

[0053] Step S308: Based on the channel magnetic field signal to be compensated, the difference information of the positioning distance between the magnetic field signal and the channel to be compensated, and the preset channel magnetic field compensation coefficient, the channel magnetic field signal to be compensated is subjected to attenuation compensation processing to obtain the channel magnetic field compensation signal.

[0054] In this embodiment, the preset channel magnetic field compensation coefficient can be set manually or based on the attenuation characteristics of the magnetic field with distance. It can be achieved by multiplying the difference in positioning distance between the magnetic field signal and the channel to be compensated by the preset channel magnetic field compensation coefficient, using the multiplication result as the compensation value. The calculated compensation value is then used to correct the intensity of the magnetic field signal of the channel to be compensated, ensuring that the compensated signal conforms to the magnetic field characteristics expected for that sub-path location.

[0055] Step S309: Generate channel magnetic field positioning information based on the channel magnetic field compensation signal, the channel magnetic field signal time alignment information corresponding to the minimum value of the multiple channel measurement sub-path attribution determination distance information, and the channel measurement sub-path information corresponding to the minimum value of the multiple channel measurement sub-path attribution determination distance information.

[0056] In this embodiment, the channel magnetic field compensation signal can be bound with the corresponding channel magnetic field signal time alignment information and channel measurement sub-path information to form spatially compensated channel magnetic field positioning information, ensuring that even if the positioning point deviates to a certain extent, it can still be accurately associated with the corresponding sub-path.

[0057] The waterway surveying method provided in this application first eliminates time deviation through time alignment processing, then clarifies the spatial association between the positioning information and each sub-path by calculating the distance, and achieves accurate sub-path assignment by combining threshold judgment. For cases exceeding the threshold, the degree of deviation is quantified by difference calculation, and the magnetic field signal is compensated in a targeted manner to ensure that even if there is a positioning deviation, the magnetic field signal can still be accurately associated with the corresponding sub-path. This strengthens the spatial binding between the waterway magnetic field signal and the aerial survey path, reduces the impact of positioning error on data association, and makes the generated waterway magnetic field positioning information more consistent with the actual spatial distribution. This provides an accurate spatial reference for subsequent analysis and processing, thereby improving the reliability of terrain identification and leakage detection in waterway surveying.

[0058] Figure 4The flowchart illustrating the implementation of the waterway surveying method provided in Embodiment 4 of this application is shown. The difference between this method and Embodiment 1 is that step S103 specifically includes: Step S401: Based on multiple preset channel magnetic field positioning feature extraction vectors, feature extraction processing is performed on the channel magnetic field positioning information to obtain channel magnetic field strength feature information, channel magnetic field frequency response feature information, and channel spatial location feature information; the channel magnetic field strength feature information, channel magnetic field frequency response feature information, and channel spatial location feature information correspond one-to-one.

[0059] In this embodiment, the multiple preset channel magnetic field positioning feature extraction vectors can be set manually or based on the physical characteristics of the magnetic field signal. They can be used to extract the magnetic field strength amplitude, signal response at different frequencies, and corresponding three-dimensional coordinate data from the channel magnetic field positioning information, namely, channel magnetic field strength feature information, channel magnetic field frequency response feature information, and channel spatial position feature information. The channel magnetic field strength feature information reflects the change in the strength of the magnetic field, the channel magnetic field frequency response feature information reflects the amplitude ratio of the signal at the transmission frequency, and the channel spatial position feature information corresponds to specific spatial coordinates.

[0060] Step S402: Calculate the difference between the channel magnetic field strength characteristic information and the preset channel magnetic field strength characteristic calibration value to obtain the channel magnetic field strength characteristic deviation value.

[0061] In this embodiment, the preset calibration value of the channel magnetic field strength characteristic can be set manually, and can refer to the average magnetic field strength when the dam is leak-free. The deviation value of the channel magnetic field strength characteristic obtained by subtracting this calibration value from the channel magnetic field strength characteristic information can be used to quantify the degree of abnormality of the magnetic field strength. The larger the deviation value, the more significant the deviation of the magnetic field strength from the normal state, which may be related to the distortion of the current field caused by leakage.

[0062] Step S403: The channel magnetic field strength characteristic deviation value, channel magnetic field frequency response characteristic information and channel spatial location characteristic information are fused and normalized to generate channel magnetic field positioning characteristic information.

[0063] In this embodiment, the deviation value of the channel magnetic field strength, the frequency response characteristic information of the channel magnetic field, and the spatial location characteristic information of the channel can be combined into a comprehensive feature vector according to a preset weight. Then, the feature components are mapped to the 0-1 interval through normalization processing to eliminate the influence of different dimensions. The resulting channel magnetic field positioning feature information can comprehensively reflect the abnormal characteristics of the magnetic field and the spatial location correlation.

[0064] Step S404: Generate multiple initial channel magnetic field positioning feature analysis pulse amplitudes based on the channel magnetic field positioning feature information, the preset channel magnetic field positioning feature analysis pulse release time slot, and the preset channel magnetic field positioning feature analysis pulse generation function.

[0065] In this embodiment, the preset channel magnetic field positioning feature analysis pulse emission slot can be a fixed time window preset by the user, such as 100ms. The preset channel magnetic field positioning feature analysis pulse generation function can be set manually, and can be constructed based on a LIF model of a spiking neural network. It generates the corresponding initial channel magnetic field positioning feature analysis pulse amplitude according to the input intensity of the channel magnetic field positioning feature information; the more significant the feature, the larger the pulse amplitude. Alternatively, the channel magnetic field positioning feature information can be used as the independent variable of the channel magnetic field positioning feature analysis pulse generation function. Through the calculation of the channel magnetic field positioning feature analysis pulse generation function, multiple initial channel magnetic field positioning feature analysis pulse amplitudes are generated within the preset channel magnetic field positioning feature analysis pulse emission slot.

[0066] Step S405: Determine whether the amplitude of the initial channel magnetic field positioning feature analysis pulse is greater than the preset channel magnetic field positioning feature analysis pulse amplitude threshold; if yes, proceed to step S406; if no, skip the initial channel magnetic field positioning feature analysis pulse amplitude.

[0067] In this embodiment, the preset threshold for the pulse amplitude of the channel magnetic field positioning feature analysis can be set manually, or it can be set based on the pulse response of a non-leaking dam. This threshold is used to filter out pulses with significant characteristics. When the initial channel magnetic field positioning feature analysis pulse amplitude exceeds the threshold, it indicates that the corresponding magnetic field feature may be related to dam leakage and requires further processing; otherwise, it is considered an interference signal and can be skipped.

[0068] Step S406: Use the initial channel magnetic field positioning feature analysis pulse amplitude as the target channel magnetic field positioning feature analysis pulse amplitude.

[0069] In this embodiment, the amplitude of the initial channel magnetic field positioning feature analysis pulse exceeding a preset threshold can be determined as the amplitude of the target channel magnetic field positioning feature analysis pulse. These pulse amplitudes correspond to magnetic field features suspected of leakage, providing effective signals for subsequent identification.

[0070] Step S407: Count the number of analytical pulse amplitudes of the target channel magnetic field positioning feature to obtain the target channel magnetic field positioning feature analytical pulse quantity information.

[0071] In this embodiment, the amplitude of the analytical pulses for the magnetic field positioning feature of the target channel can be counted. The number of analytical pulses for the magnetic field positioning feature of the target channel reflects the frequency of occurrence of significant leakage features per unit time. The more pulses there are, the denser the leakage features are.

[0072] Step S408: Based on the target channel magnetic field positioning feature analysis pulse quantity information and the preset channel magnetic field positioning feature analysis pulse emission time slot, obtain the channel magnetic field positioning feature analysis pulse emission rate information.

[0073] In this embodiment, the number of target channel magnetic field positioning feature analysis pulses can be divided by a preset channel magnetic field positioning feature analysis pulse emission time slot to obtain channel magnetic field positioning feature analysis pulse emission rate information, which can quantify the pulse emission intensity per unit time and is used to reflect the significance of leakage characteristics.

[0074] Step S409: Based on the channel magnetic field positioning feature analysis pulse emission rate information, the channel magnetic field positioning feature information corresponding to the channel magnetic field positioning feature analysis pulse emission rate information, and the preset channel magnetic field positioning feature analysis pulse emission rate threshold, channel terrain identification information and initial channel dam leakage identification information are obtained.

[0075] In this embodiment, a preset threshold for the pulse emission rate of the channel magnetic field positioning feature analysis can be used to distinguish between leakage features and normal terrain features. When the pulse emission rate of the channel magnetic field positioning feature analysis is greater than the threshold, it is marked as the initial channel dam leakage identification information based on the spatial location in the corresponding channel magnetic field positioning feature information; otherwise, channel terrain identification information is generated based on the spatial location features to reflect the terrain features of the channel.

[0076] The waterway measurement method provided in this application, through multi-dimensional feature extraction and deep analysis, accurately identifies leakage features and topographic features in magnetic field signals, improves the distinguishability and accuracy of initial waterway dam leakage identification information and waterway topographic identification information, lays a high-quality data foundation for subsequent optimization processing, and further improves the sensitivity of leakage detection and the accuracy of waterway topographic identification in waterway measurement.

[0077] Figure 5 The flowchart illustrating the implementation of the waterway surveying method provided in Embodiment 5 of this application is shown. Its difference from Embodiment 4 described above lies in: Multiple preset channel magnetic field positioning feature extraction vectors include preset channel magnetic field intensity feature extraction vectors, preset channel magnetic field frequency response feature extraction vectors, and preset channel spatial position feature extraction vectors. Step S401 specifically includes: Step S501: Based on the preset channel magnetic field strength feature extraction vector, perform feature extraction processing on the channel magnetic field positioning information to obtain the channel magnetic field strength feature vector.

[0078] In this embodiment, the preset channel magnetic field strength feature extraction vector, the preset channel magnetic field frequency response feature extraction vector, and the preset channel spatial location feature extraction vector can all be manually set. The preset channel magnetic field strength feature extraction vector can be set based on the amplitude characteristics of the three-dimensional components of the magnetic field. It can be obtained by performing a convolution operation with the magnetic field strength data in the channel magnetic field positioning information to extract the amplitude variation features of the magnetic field strength in different spatial directions, forming a channel magnetic field strength feature vector containing information on the magnitude and gradient of the magnetic field strength.

[0079] Step S502: Based on the preset channel magnetic field frequency response feature extraction vector, the channel magnetic field positioning information is processed by feature extraction to obtain the channel magnetic field frequency response feature vector.

[0080] In this embodiment, the preset channel magnetic field frequency response feature extraction vector can be set according to the transmission frequency and harmonic characteristics. It can be used to filter and feature map the frequency domain data in the channel magnetic field positioning information, extract the amplitude ratio, phase shift and other features of the transmission frequency component, and form a channel magnetic field frequency response feature vector that reflects the frequency response characteristics.

[0081] Step S503: Based on the preset channel spatial location feature extraction vector, the channel magnetic field positioning information is processed to extract features and obtain the channel spatial location feature vector.

[0082] In this embodiment, the preset channel spatial location feature extraction vector can be the coordinate parameters of the corresponding channel three-dimensional coordinate system. By extracting the spatial coordinate data in the channel magnetic field positioning information and combining it with the segment division in the preset channel measurement path information, a channel spatial location feature vector containing position coordinates and segment affiliation is formed.

[0083] Step S504: The channel magnetic field strength feature vector and the channel magnetic field frequency response feature vector are interactively processed to obtain the channel magnetic field strength frequency interactive feature vector.

[0084] In this embodiment, the correlation features between magnetic field strength anomalies and frequency response anomalies can be fused by calculating the dot product of the channel magnetic field strength feature vector and the channel magnetic field frequency response feature vector, thereby forming a channel magnetic field strength frequency interaction feature vector that reflects the coordinated change of "strength-frequency", thus highlighting the synchronous distortion of magnetic field strength and frequency caused by leakage.

[0085] Step S505: Obtain the channel magnetic field strength feature information based on the channel magnetic field strength frequency interaction feature vector and the channel magnetic field strength feature vector.

[0086] In this embodiment, the channel magnetic field strength frequency interaction feature vector and the channel magnetic field strength feature vector can be superimposed with a preset weight to enhance the intensity anomaly features related to the frequency response and form channel magnetic field strength feature information that comprehensively reflects the magnetic field strength characteristics.

[0087] Step S506: Based on the channel magnetic field strength frequency interaction feature vector and the channel magnetic field frequency response feature vector, obtain the channel magnetic field frequency response feature information.

[0088] In this embodiment, the channel magnetic field strength frequency interaction feature vector and the channel magnetic field frequency response feature vector can be superimposed with a preset weight to highlight the frequency features related to the intensity anomaly, forming channel magnetic field frequency response feature information that comprehensively reflects the magnetic field frequency response characteristics.

[0089] Step S507: Perform format conversion processing on the channel spatial location feature vector to obtain channel spatial location feature information.

[0090] In this embodiment, the channel spatial location feature vector can be converted into a standardized coordinate format that matches the local coordinate system, eliminating the influence of differences in coordinate systems of different channels, and forming channel spatial location feature information that can be directly used for spatial association.

[0091] The waterway measurement method provided in this application extracts the corresponding feature vectors from the waterway magnetic field positioning information and performs interactive processing to accurately capture the coordinated anomalies of magnetic field strength and frequency response when the dam leaks. This significantly improves the pertinence and accuracy of feature extraction, greatly enhances the distinguishability between waterway topography identification information and initial waterway dam leakage identification information, and ensures the reliability of waterway dam leakage identification results.

[0092] Figure 6 The flowchart illustrating the implementation of the waterway surveying method provided in Embodiment Six of this application is shown. The difference between this method and Embodiment Four is that step S409 specifically includes: Step S601: Determine whether the channel magnetic field positioning feature analysis pulse emission rate information is greater than the preset channel magnetic field positioning feature analysis pulse emission rate threshold; if yes, proceed to step S602; if no, proceed to step S603.

[0093] In this embodiment, the preset threshold for the pulse emission rate of the channel magnetic field positioning feature analysis can be set manually. It can be determined based on the pulse emission rate statistics of non-leaking areas and known leaking areas. It is used to distinguish between leaking features and normal terrain features. When the pulse emission rate information of the channel magnetic field positioning feature analysis exceeds the threshold, it indicates that the corresponding magnetic field feature is more likely to be related to dam leakage.

[0094] Step S602: Determine the channel magnetic field positioning feature information corresponding to the pulse firing rate information of the channel magnetic field positioning feature analysis as an abnormal feature of channel dam leakage.

[0095] In this embodiment, when the pulse emission rate information of the channel magnetic field positioning feature analysis is greater than the preset pulse emission rate threshold of the channel magnetic field positioning feature analysis, it indicates that the features such as abnormal magnetic field strength and frequency response distortion contained in the channel magnetic field positioning feature information are highly consistent with the changes in the current field caused by leakage. Therefore, it is determined to be an abnormal feature of channel dam leakage and marked as feature data of suspected leakage area.

[0096] Step S603: Determine the channel magnetic field positioning feature information corresponding to the pulse firing rate information of the channel magnetic field positioning feature analysis as a normal feature of channel measurement.

[0097] In this embodiment, when the pulse emission rate information of the channel magnetic field positioning feature analysis is not greater than the preset pulse emission rate threshold of the channel magnetic field positioning feature analysis, it indicates that the magnetic field signal corresponding to the channel magnetic field positioning feature information has not shown any significant abnormalities related to leakage, and is consistent with the magnetic field distribution law of normal channel and dam area. Therefore, it is determined to be a normal feature of channel measurement, corresponding to a normal terrain area.

[0098] Step S604: Perform multi-dimensional reconstruction processing on the abnormal leakage characteristics of the waterway embankment and the normal characteristics of waterway measurement to obtain waterway topography identification information and initial waterway embankment leakage identification information.

[0099] In this embodiment, for the abnormal leakage characteristics of the waterway embankment, combined with the spatial location characteristics of the waterway contained therein, the spatial distribution of suspected leakage points can be reconstructed through three-dimensional modeling to form initial waterway embankment leakage identification information, and the coordinates and feature intensity of each abnormal point are marked; for the normal characteristics of waterway measurement, the topographic features can be integrated based on its spatial location information to reconstruct topographic elements such as water depth, shoreline, and embankment surface elevation, and generate waterway topographic identification information, so as to achieve accurate differentiation and structured presentation of the two types of information.

[0100] The waterway measurement method provided in this application strengthens the boundary distinction between waterway topographic identification information and initial waterway embankment leakage identification information, ensuring accurate extraction of leakage anomaly features and complete preservation of normal topographic features, providing a clearer feature basis for subsequent optimization processing, and further improving the accuracy of leakage detection and the completeness of topographic identification in waterway measurement.

[0101] Figure 7 The flowchart illustrating the implementation of the waterway surveying method provided in Embodiment Seven of this application is shown. The difference between this method and Embodiment One described above is that step S104 specifically includes: Step S701: Based on the preset number of initial channel dam leakage identification information groups, randomly extract the initial channel dam leakage identification information to obtain multiple initial channel dam leakage identification group center information.

[0102] In this embodiment, the number of preset initial channel dam seepage identification information groups can be set manually, or can be set manually according to the distribution characteristics of suspected seepage areas of the dam. The coordinates of a corresponding number of suspected seepage points can be randomly selected from the initial channel dam seepage identification information as the initial grouping center. Each center represents the initial core position of a potential seepage channel, providing a benchmark for subsequent grouping.

[0103] Step S702: Based on the multiple initial channel dam leakage identification grouping center information, the initial channel dam leakage identification information is grouped to obtain multiple initial channel dam leakage identification information sets; the initial channel dam leakage identification information sets include multiple initial channel dam leakage identification elements.

[0104] In this embodiment, the spatial distance between each initial channel dam leakage identification element and each initial grouping center can be calculated, and each element can be assigned to the set corresponding to the nearest grouping center to form multiple initial channel dam leakage identification information sets. Each set represents a group of spatially close suspected leakage points, corresponding to a potential leakage channel cluster.

[0105] Step S703: Calculate the logical distance between multiple initial channel dam seepage identification elements to obtain the distance information of multiple initial channel dam seepage identification elements.

[0106] In this embodiment, the logical distance can be Euclidean distance, which can be used to comprehensively reflect the spatial proximity and feature similarity between multiple initial channel dam leakage identification elements. The obtained distance information of the initial channel dam leakage identification elements is used to measure the degree of aggregation of elements in the set.

[0107] Step S704: Based on the multiple initial channel dam leakage identification information sets and the distance information of the multiple initial channel dam leakage identification elements, obtain the multiple target channel dam leakage identification group center information.

[0108] In this embodiment, for each initial channel dam leakage identification information set, the mean coordinates and mean features of all initial channel dam leakage identification elements in the set can be calculated, and weighted adjustment can be performed in combination with element distance information to obtain a new grouping center, namely the target channel dam leakage identification grouping center information, so that the new center is more in line with the overall distribution of elements in the set.

[0109] Step S705: Determine whether the difference between the multiple target channel dam leakage identification group center information and the multiple initial channel dam leakage identification group center information is greater than the preset channel dam leakage identification group center offset threshold; if yes, proceed to step S706; if no, proceed to step S707.

[0110] In this embodiment, the preset threshold for the offset of the navigation channel dam seepage identification group center can be set manually or based on the positioning accuracy of the UAV, and can be used to determine whether the group center is stabilizing. The difference between the target navigation channel dam seepage identification group center information and the initial navigation channel dam seepage identification group center information is calculated. If the difference is greater than the preset threshold for the offset of the navigation channel dam seepage identification group center, it indicates that the navigation channel dam seepage identification group center information still needs to be optimized; otherwise, it is considered that the navigation channel dam seepage identification group center information has stabilized.

[0111] Step S706: Use the multiple target channel dam leakage identification group center information as multiple initial channel dam leakage identification group center information, and return to step S702.

[0112] In this embodiment, the difference between the target channel dam leakage identification group center information and the initial channel dam leakage identification group center information is calculated. If the difference is greater than the preset channel dam leakage identification group center offset threshold, the original initial group center is replaced with the newly obtained target channel dam leakage identification group center information, and the grouping process is re-executed. Through iteration, the group center gradually converges to a better position, thereby improving the aggregation degree of elements within the set.

[0113] Step S707: Based on the difference between the multiple target channel dam leakage identification group center information and the multiple initial channel dam leakage identification group center information, the multiple initial channel dam leakage identification information sets are numerically adjusted to obtain multiple target channel dam leakage identification information sets.

[0114] In this embodiment, the offset difference of the grouping center is used to correct the coordinates and optimize the features of the elements in the initial waterway dam leakage identification information set, so that the elements are closer to the target grouping center, eliminating the deviation caused by the initial random selection, and forming a more compact target waterway dam leakage identification information set.

[0115] Step S708: Based on the multiple sets of target channel dam leakage identification information, obtain the target channel dam leakage identification information.

[0116] In this embodiment, for each target channel dam seepage identification information set, the target group center coordinates are extracted as the core location of the seepage channel, the average inversion current of the elements in the set is statistically analyzed to calculate the seepage flow, and the core location, seepage flow and feature information of all sets are integrated to form complete target channel dam seepage identification information.

[0117] The waterway measurement method provided in this application aggregates suspected points in the initial waterway embankment leakage identification information into a stable cluster based on space and features, accurately locates the core area of ​​the leakage channel, ensures that the optimization results conform to the distribution law of the current field and the seepage field, effectively improves the accuracy and reliability of the target waterway embankment leakage identification information, and provides high-quality leakage data support for the generation of waterway measurement information.

[0118] Corresponding to the method in the above embodiments, Figure 8 A structural block diagram of the waterway surveying device provided in the embodiments of this application is shown. For ease of explanation, only the parts related to the embodiments of this application are shown. Figure 8 The example waterway measurement device can be the execution subject of the waterway measurement method provided in the aforementioned embodiment 1.

[0119] Reference Figure 8 The waterway surveying device includes: The information acquisition module 810 is used to acquire channel magnetic field signal information and channel positioning information; The channel magnetic field positioning information generation module 820 is used to perform spatiotemporal synchronization processing on the channel magnetic field signal information, channel positioning information and preset channel measurement path information to generate channel magnetic field positioning information. The channel topography identification information and initial channel dam leakage identification information generation module 830 is used to analyze and process the channel magnetic field positioning information to obtain channel topography identification information and initial channel dam leakage identification information. The target channel dam seepage identification information generation module 840 is used to optimize the initial channel dam seepage identification information to obtain the target channel dam seepage identification information. The waterway measurement information generation module 850 is used to generate waterway measurement information based on the target waterway dam seepage identification information and waterway topography identification information.

[0120] For details on how each module in the waterway surveying device provided in this application implements its respective function, please refer to the foregoing. Figure 1 The description of Embodiment 1 shown will not be repeated here.

[0121] It should be understood that the sequence number of each step in the above embodiments does not imply the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of this application.

[0122] It should be understood that, when used in this application specification and the appended claims, the term "comprising" indicates the presence of the described features, integrals, steps, operations, elements and / or components, but does not exclude the presence or addition of one or more other features, integrals, steps, operations, elements, components and / or a collection thereof.

[0123] It should also be understood that the term “and / or” as used in this application specification and the appended claims means any combination of one or more of the associated listed items and all possible combinations, and includes such combinations.

[0124] As used in this application specification and the appended claims, the term "if" may be interpreted, depending on the context, as "when," "once," "in response to determination," or "in response to detection." Similarly, the phrase "if determined" or "if detected [the described condition or event]" may be interpreted, depending on the context, as meaning "once determined," "in response to determination," "once detected [the described condition or event]," or "in response to detection [the described condition or event]."

[0125] Furthermore, in the description of this application and the appended claims, the terms "first," "second," "third," etc., are used only for distinguishing descriptions and should not be construed as indicating or implying relative importance. It should also be understood that although the terms "first," "second," etc., are used in the text to describe various elements in some embodiments of this application, these elements should not be limited by these terms. These terms are merely used to distinguish one element from another. For example, a first table may be named a second table, and similarly, a second table may be named a first table, without departing from the scope of the various described embodiments. Both the first table and the second table are tables, but they are not the same table.

[0126] References to "one embodiment" or "some embodiments" as described in this specification mean that one or more embodiments of this application include a specific feature, structure, or characteristic described in connection with that embodiment. Therefore, the phrases "in one embodiment," "in some embodiments," "in other embodiments," "in still other embodiments," etc., appearing in different parts of this specification do not necessarily refer to the same embodiment, but rather mean "one or more, but not all, embodiments," unless otherwise specifically emphasized. The terms "comprising," "including," "having," and variations thereof mean "including but not limited to," unless otherwise specifically emphasized.

[0127] The waterway measurement method provided in this application can be applied to terminal devices such as mobile phones, tablets, wearable devices, vehicle-mounted devices, augmented reality (AR) / virtual reality (VR) devices, laptops, ultra-mobile personal computers (UMPCs), netbooks, and personal digital assistants (PDAs). This application does not impose any restrictions on the specific type of terminal device.

[0128] For example, the terminal device may be a station (STAION, ST) in a WLAN, a cellular phone, a cordless phone, a Session Initiation Protocol (SIP) phone, a Wireless Local Loop (WLL) station, a Personal Digital Assistant (PDA) device, a handheld device with wireless communication capabilities, a computing device or other processing device connected to a wireless modem, an in-vehicle device, a vehicle networking terminal, a computer, a laptop computer, a handheld communication device, a handheld computing device, a satellite wireless device, a wireless modem card, a set-top box (STB), customer premises equipment (CPE), and / or other devices used for communication over a wireless system, as well as next-generation communication systems, such as mobile terminals in 5G networks or mobile terminals in future evolved Public Land Mobile Network (PLMN) networks.

[0129] As an example and not a limitation, when the terminal device is a wearable device, the term "wearable device" can also refer to any device that utilizes wearable technology to intelligently design and develop everyday wearables, such as glasses, gloves, watches, clothing, and shoes. Wearable devices are portable devices worn directly on the body or integrated into a user's clothing or accessories. Wearable devices are not merely hardware devices; they achieve powerful functions through software support, data interaction, and cloud interaction. Broadly defined, wearable smart devices include those with comprehensive functions, large sizes, and the ability to perform complete or partial functions without relying on a smartphone, such as smartwatches or smart glasses, as well as those focused on a specific application function that require interaction with other devices such as smartphones, such as various smart bracelets and smart jewelry for vital sign monitoring.

[0130] Figure 9 This is a schematic diagram of the structure of a terminal device provided in an embodiment of this application. For example... Figure 9 As shown, the terminal device 9 of this embodiment includes: at least one processor 90 ( Figure 9 (Only one is shown in the image) A memory 91 stores a computer program 92 that can run on the processor 90. When the processor 90 executes the computer program 92, it implements the steps in the various waterway measurement method embodiments described above, for example... Figure 1 Steps S101 to S105 are shown. Alternatively, when the processor 90 executes the computer program 92, it implements the functions of each module / unit in the above-described device embodiments, for example... Figure 8 The functions of modules 810 to 850 are shown.

[0131] The terminal device 9 can be a desktop computer, laptop, handheld computer, or cloud server, etc. The terminal device may include, but is not limited to, a processor 90 and a memory 91. Those skilled in the art will understand that... Figure 9 This is merely an example of terminal device 9 and does not constitute a limitation on terminal device 9. It may include more or fewer components than shown, or combine certain components, or different components. For example, the terminal device may also include input transmission devices, network access devices, buses, etc.

[0132] The processor 90 may be a Central Processing Unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor may be a microprocessor or any conventional processor.

[0133] In some embodiments, the memory 91 may be an internal storage unit of the terminal device 9, such as a hard disk or memory of the terminal device 9. The memory 91 may also be an external storage device of the terminal device 9, such as a plug-in hard disk, smart media card (SMC), secure digital card (SD), flash card, etc., equipped on the terminal device 9. Furthermore, the memory 91 may include both internal and external storage units of the terminal device 9. The memory 91 is used to store the operating system, applications, bootloader, data, and other programs, such as the program code of the computer program. The memory 91 can also be used to temporarily store data that has been sent or will be sent.

[0134] Furthermore, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0135] This application also provides a terminal device, which includes at least one memory, at least one processor, and a computer program stored in the at least one memory and executable on the at least one processor. When the processor executes the computer program, it causes the terminal device to implement the steps in any of the above method embodiments.

[0136] This application also provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the steps described in the various method embodiments above.

[0137] This application provides a computer program product that, when run on a terminal device, enables the terminal device to implement the steps described in the various method embodiments above.

[0138] If the integrated module / unit is implemented as 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, all or part of the processes in the methods of the above embodiments can also be implemented by a computer program instructing related hardware. The computer program can be stored in a computer-readable storage medium, and when executed by a processor, it can implement the steps of the various method embodiments described above. The computer program includes computer program code, which can be in the form of source code, object code, executable files, or certain intermediate forms. The computer-readable medium can include: any entity or device capable of carrying the computer program code, a recording medium, a USB flash drive, a portable hard drive, a magnetic disk, an optical disk, a computer memory, a read-only memory (ROM), a random access memory (RAM), an electrical carrier signal, a telecommunication signal, and a software distribution medium, etc.

[0139] In the above embodiments, the descriptions of each embodiment have different focuses. For parts that are not described in detail or recorded in a certain embodiment, please refer to the relevant descriptions of other embodiments.

[0140] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0141] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0142] The above-described embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit them. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of this application, and should all be included within the protection scope of this application.

Claims

1. A method for waterway surveying, characterized in that, include: Acquire channel magnetic field signal information and channel positioning information; The channel magnetic field signal information, channel positioning information, and preset channel measurement path information are processed in a time-space synchronization manner to generate channel magnetic field positioning information. The channel magnetic field positioning information is analyzed and processed to obtain channel topography identification information and initial channel dam leakage identification information; The initial channel dam leakage identification information is optimized to obtain the target channel dam leakage identification information; Based on the target waterway dam seepage identification information and waterway topography identification information, waterway measurement information is generated.

2. The waterway surveying method as described in claim 1, characterized in that, The step of performing spatiotemporal synchronization processing on the channel magnetic field signal information, channel positioning information, and preset channel measurement path information to generate channel magnetic field positioning information specifically includes: Time information is extracted from the channel magnetic field signal information and channel positioning information to generate multiple channel magnetic field signal time information and multiple channel positioning time information; the channel magnetic field signal time information and the channel positioning time information correspond one-to-one. Calculate the difference between the time information of the multiple channel magnetic field signals and the time information of the multiple channel positioning to obtain the time difference information of the multiple channel magnetic field positioning. Determine whether the channel magnetic field positioning time difference information is greater than a preset channel magnetic field positioning time difference threshold; If so, delete the channel magnetic field signal time information and channel positioning time information corresponding to the channel magnetic field positioning time difference information; If not, then based on the channel magnetic field signal time information and channel positioning time information corresponding to the channel magnetic field positioning time difference information, channel magnetic field signal effective time information and channel positioning effective time information are generated. Based on the channel magnetic field signal information corresponding to the effective time information of the channel magnetic field signal, the channel positioning information corresponding to the effective time information of the channel positioning, and the preset channel measurement path information, spatiotemporal synchronization processing is performed to generate channel magnetic field positioning information.

3. The waterway surveying method as described in claim 2, characterized in that, The preset waterway survey path information includes multiple preset waterway survey sub-path information; The step of generating channel magnetic field positioning information by performing spatiotemporal synchronization processing based on the channel magnetic field signal information corresponding to the channel magnetic field signal effective time information, the channel positioning information corresponding to the channel positioning effective time information, and the preset channel measurement path information, specifically includes: Time alignment processing is performed on the channel magnetic field signal information corresponding to the effective time information of the channel magnetic field signal and the channel positioning information corresponding to the effective time information of channel positioning to obtain channel magnetic field signal time alignment information and channel positioning time alignment information; the channel magnetic field signal time alignment information and the channel positioning time alignment information correspond one-to-one. Calculate the distance between the channel positioning time alignment information and multiple preset channel measurement sub-path information to obtain multiple channel measurement sub-path attribution determination distance information; Determine whether the minimum value of the multiple waterway measurement sub-path attribution determination distance information is less than a preset waterway measurement sub-path attribution determination distance threshold; If so, then channel magnetic field positioning information is generated based on the channel magnetic field signal time alignment information corresponding to the minimum value of the multiple channel measurement sub-path attribution determination distance information, the channel measurement sub-path information corresponding to the minimum value of the multiple channel measurement sub-path attribution determination distance information, and the channel magnetic field signal time alignment information corresponding to the minimum value of the multiple channel measurement sub-path attribution determination distance information. If not, calculate the difference between the minimum value of the waterway measurement sub-path attribution determination distance information and the preset waterway measurement sub-path attribution determination distance threshold to obtain the magnetic field signal waterway positioning distance difference information to be compensated. The channel positioning time alignment information corresponding to the minimum value of the multiple channel measurement sub-path attribution determination distance information is used as the channel positioning information of the magnetic field signal to be compensated. The channel magnetic field signal time alignment information corresponding to the channel positioning information of the magnetic field signal to be compensated is taken as the channel magnetic field signal to be compensated. Based on the channel magnetic field signal to be compensated, the difference information of the positioning distance between the magnetic field signal and the channel positioning distance to be compensated, and the preset channel magnetic field compensation coefficient, the channel magnetic field signal to be compensated is subjected to attenuation compensation processing to obtain the channel magnetic field compensation signal. Based on the channel magnetic field compensation signal, the channel magnetic field signal time alignment information corresponding to the minimum value of the multiple channel measurement sub-path attribution determination distance information, and the channel measurement sub-path information corresponding to the minimum value of the multiple channel measurement sub-path attribution determination distance information, channel magnetic field positioning information is generated.

4. The waterway surveying method as described in claim 1, characterized in that, The step of parsing and processing the channel magnetic field positioning information to obtain channel topography identification information and initial channel dam seepage identification information specifically includes: Based on multiple preset channel magnetic field positioning feature extraction vectors, feature extraction processing is performed on the channel magnetic field positioning information to obtain channel magnetic field intensity feature information, channel magnetic field frequency response feature information, and channel spatial location feature information; the channel magnetic field intensity feature information, channel magnetic field frequency response feature information, and channel spatial location feature information correspond one-to-one. The difference between the channel magnetic field strength characteristic information and the preset channel magnetic field strength characteristic calibration value is calculated to obtain the channel magnetic field strength characteristic deviation value; The channel magnetic field strength characteristic deviation value, channel magnetic field frequency response characteristic information and channel spatial location characteristic information are fused and normalized to generate channel magnetic field positioning characteristic information. Based on the channel magnetic field positioning feature information, the preset channel magnetic field positioning feature analysis pulse release time slot, and the preset channel magnetic field positioning feature analysis pulse generation function, multiple initial channel magnetic field positioning feature analysis pulse amplitudes are generated. When the amplitude of the initial channel magnetic field positioning feature analysis pulse is greater than the preset channel magnetic field positioning feature analysis pulse amplitude threshold, the amplitude of the initial channel magnetic field positioning feature analysis pulse is taken as the amplitude of the target channel magnetic field positioning feature analysis pulse. The number of analytical pulse amplitudes of the target channel magnetic field positioning feature is counted to obtain the target channel magnetic field positioning feature analytical pulse quantity information. Based on the target channel magnetic field positioning feature analysis pulse quantity information and the preset channel magnetic field positioning feature analysis pulse emission time slot, the channel magnetic field positioning feature analysis pulse emission rate information is obtained. Based on the channel magnetic field positioning feature analysis pulse emission rate information, the channel magnetic field positioning feature information corresponding to the channel magnetic field positioning feature analysis pulse emission rate information, and the preset channel magnetic field positioning feature analysis pulse emission rate threshold, channel terrain identification information and initial channel dam leakage identification information are obtained.

5. The waterway surveying method as described in claim 4, characterized in that, Multiple preset channel magnetic field positioning feature extraction vectors include preset channel magnetic field intensity feature extraction vectors, preset channel magnetic field frequency response feature extraction vectors, and preset channel spatial position feature extraction vectors. The step of extracting features from the channel magnetic field positioning information based on multiple preset channel magnetic field positioning feature extraction vectors to obtain channel magnetic field intensity feature information, channel magnetic field frequency response feature information, and channel spatial location feature information specifically includes: Based on the preset channel magnetic field strength feature extraction vector, the channel magnetic field positioning information is processed to extract features and obtain the channel magnetic field strength feature vector. Based on the preset channel magnetic field frequency response feature extraction vector, the channel magnetic field positioning information is processed to extract features and obtain the channel magnetic field frequency response feature vector. Based on the preset channel spatial location feature extraction vector, the channel magnetic field positioning information is processed to extract features, and the channel spatial location feature vector is obtained. The channel magnetic field strength feature vector and the channel magnetic field frequency response feature vector are interactively processed to obtain the channel magnetic field strength frequency interactive feature vector. Based on the frequency interaction feature vector and the feature vector of the channel magnetic field strength, the feature information of the channel magnetic field strength is obtained. Based on the channel magnetic field intensity frequency interaction feature vector and the channel magnetic field frequency response feature vector, the channel magnetic field frequency response feature information is obtained. The spatial location feature vector of the waterway is converted to obtain the spatial location feature information of the waterway.

6. The waterway surveying method as described in claim 4, characterized in that, The step of obtaining channel topography identification information and initial channel dam leakage identification information based on the channel magnetic field positioning feature analysis pulse emission rate information, the channel magnetic field positioning feature information corresponding to the channel magnetic field positioning feature analysis pulse emission rate information, and the preset channel magnetic field positioning feature analysis pulse emission rate threshold specifically includes: Determine whether the pulse emission rate information of the channel magnetic field positioning feature analysis is greater than the preset pulse emission rate threshold of the channel magnetic field positioning feature analysis; If so, the channel magnetic field positioning feature information corresponding to the pulse firing rate information of the channel magnetic field positioning feature analysis is determined to be an abnormal feature of channel dam leakage. If not, the channel magnetic field positioning feature information corresponding to the pulse firing rate information of the channel magnetic field positioning feature analysis is determined to be a normal feature of channel measurement. The abnormal leakage characteristics of the waterway embankment and the normal characteristics of waterway measurement are reconstructed in multiple dimensions to obtain waterway topography identification information and initial waterway embankment leakage identification information.

7. The waterway surveying method as described in claim 1, characterized in that, The step of optimizing the initial channel dam leakage identification information to obtain the target channel dam leakage identification information specifically includes: Based on the preset number of initial channel dam leakage identification information groups, the initial channel dam leakage identification information is randomly sampled to obtain multiple initial channel dam leakage identification group center information. Based on the multiple initial channel dam leakage identification group center information, the initial channel dam leakage identification information is grouped to obtain multiple initial channel dam leakage identification information sets; the initial channel dam leakage identification information sets include multiple initial channel dam leakage identification elements. Calculate the logical distance between multiple initial channel dam seepage identification elements to obtain the distance information of multiple initial channel dam seepage identification elements; Based on the multiple initial channel dam seepage identification information sets and the distance information of multiple initial channel dam seepage identification elements, multiple target channel dam seepage identification group center information are obtained; Determine whether the difference between the multiple target channel dam seepage identification group center information and the multiple initial channel dam seepage identification group center information is greater than the preset channel dam seepage identification group center offset threshold. If so, the multiple target channel dam leakage identification group center information is used as multiple initial channel dam leakage identification group center information, and the process is returned to the step of grouping the initial channel dam leakage identification information according to the multiple initial channel dam leakage identification group center information to obtain a set of multiple initial channel dam leakage identification information. If not, then based on the difference between the multiple target channel dam leakage identification group center information and the multiple initial channel dam leakage identification group center information, the multiple initial channel dam leakage identification information sets are numerically adjusted to obtain multiple target channel dam leakage identification information sets. Based on the set of multiple target channel dam leakage identification information, the target channel dam leakage identification information is obtained.

8. A waterway surveying device, characterized in that, include: The information acquisition module is used to acquire channel magnetic field signal information and channel positioning information; The channel magnetic field positioning information generation module is used to perform spatiotemporal synchronization processing on the channel magnetic field signal information, channel positioning information and preset channel measurement path information to generate channel magnetic field positioning information. The channel topography identification information and initial channel dam leakage identification information generation module is used to analyze and process the channel magnetic field positioning information to obtain channel topography identification information and initial channel dam leakage identification information. The target channel dam seepage identification information generation module is used to optimize the initial channel dam seepage identification information to obtain the target channel dam seepage identification information. The waterway measurement information generation module is used to generate waterway measurement information based on the target waterway dam seepage identification information and waterway topography identification information.

9. A terminal device, characterized in that, The terminal device includes a memory and a processor. The memory stores a computer program that can run on the processor. When the processor executes the computer program, it implements the steps of the method as described in any one of claims 1 to 7.

10. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by a processor, it implements the steps of the method as described in any one of claims 1 to 7.

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