Dynamic water depth measurement method, device, equipment and medium

Abstract

The invention relates to a dynamic water depth measurement method, device and equipment and a medium. The method comprises the following steps: arranging a plurality of sensors arranged in an array on a hydrofoil structure, and collecting original data through each sensor; setting a pressure threshold value, and performing quantization processing on the original data according to the pressure threshold value to obtain a binary matrix; based on the binary matrix, determining an initial estimation interval in each column of data through a boundary detection algorithm; continuously taking intersections based on the initial estimation interval, and performing arithmetic average processing on the final interval to obtain an interface estimation value of the water body and the air; and performing weighted data fusion processing on the interface estimation value to obtain the final measured water depth. According to the invention, the anti-interference capability and the measurement precision of water depth measurement in the water surface high-speed sliding process can be improved.

Description

Technical Field

[0001] The present invention relates to the technical field of water depth measurement, and in particular to a dynamic water depth measurement method, device, equipment and medium. Background Art

[0002] The Aqua-Air Cross-Medium Robot can freely switch between three motion modes: aerial flight, surface gliding, and underwater diving. During the research and development process, in order to achieve real-time, autonomous closed-loop control of these three motion modes, it was crucial to be able to sense the robot's water depth in real time during underwater diving and surface gliding, thereby determining its current navigation status. During underwater diving, the robot is completely submerged and moves solely within the water medium. The technology for determining water depth in this state is already quite mature. However, during high-speed surface gliding, the Aqua-Air Cross-Medium Robot is exposed to the interference of gas-liquid two-phase flow, and the force conditions are complex and rapidly changing, making it difficult to measure accurate real-time water depth data. Summary of the Invention

[0003] Based on this, it is necessary to provide a dynamic water depth measurement method, device, equipment and medium with strong anti-interference ability, high measurement accuracy and strong real-time performance to address the above technical problems.

[0004] A dynamic water depth measurement method comprises: providing a plurality of sensors arranged in an array on a hydrofoil structure, and collecting raw data through each sensor; Setting a pressure threshold, and performing quantization processing on the original data according to the pressure threshold to obtain a binary matrix; Based on the binary matrix, an initial estimated interval in each column of data is determined by a boundary detection algorithm; based on the initial estimated intervals, intersections are continuously taken, and arithmetic averaging is performed on the final intervals to obtain an estimated value of the interface between the water body and the air; The interface estimation value is subjected to weighted data fusion processing to obtain the final measured water depth.

[0005] A dynamic water depth measuring device, comprising: A sensor arrangement module is used to set a number of sensors arranged in an array on the hydrofoil structure and collect raw data through each sensor; a quantization processing module, configured to set a pressure threshold, and perform quantization processing on the raw data according to the pressure threshold to obtain a binary matrix; An interface estimation calculation module is configured to determine, based on the binary matrix and using a boundary detection algorithm, an initial estimation interval in each column of data; continuously take intersections based on the initial estimation intervals, and perform arithmetic averaging on the final intervals to obtain an estimated value of the interface between the water body and the air; The water depth measurement module is used to perform weighted data fusion processing on the estimated value of the interface to obtain the final measured water depth.

[0006] A computer device includes a memory and a processor. The memory stores a computer program, and when the processor executes the computer program, the steps of the dynamic water depth measurement method are implemented.

[0007] A computer-readable storage medium stores a computer program thereon. When the computer program is executed by a processor, the steps of the dynamic water depth measurement method are implemented.

[0008] Compared with the prior art, the dynamic water depth measurement method, device, equipment and medium provided by the present invention have the following effects: 1. By arranging multiple sensors in an array on the hydrofoil structure, sensing data at multiple points can be obtained simultaneously, enabling large-area synchronous sampling of the water surface, capturing more comprehensive water surface fluctuation characteristics, providing rich data for subsequent precise calculations, and having strong dynamic adaptability.

[0009] 2. Utilizing the huge difference between air pressure and water pressure, the interface between water and air can be estimated in real time, thus greatly improving the anti-interference ability of water depth measurement during high-speed water surface gliding.

[0010] 3. By setting a pressure threshold to perform quantization processing on the original data, converting the analog signal into a binary matrix, part of the random noise can be filtered out, enhancing the anti-noise ability; then, through the boundary detection algorithm, initial interval estimation is performed on each column of data to reduce systematic errors; based on the initial estimation interval, intersections are continuously taken, and arithmetic mean processing is performed on the final interval, which can effectively offset the influence brought by local data fluctuations; combined with weighted data fusion, the accuracy of water depth measurement can be greatly improved. Description of the Drawings

[0011] In order to more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the following will briefly introduce the drawings required for the description of the embodiments or the prior art. Obviously, the following drawings are only some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other drawings can be obtained based on the structures shown in these drawings.

[0012] Figure 1 It is a schematic flow chart of the dynamic water depth measurement method provided in Embodiment 1; Figure 2 It is a schematic diagram of the staggered arrangement structure of the sensors provided in Embodiment 1; Figure 3 It is a structural block diagram of the dynamic water depth measurement device provided in Embodiment 2; Figure 4Internal structure diagram of the computer device provided in Embodiment 3.

[0013] The realization of the object, functional features and advantages of the present invention will be further described in conjunction with the embodiments and with reference to the accompanying drawings. Detailed implementation manners

[0014] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0015] It should be noted that all directional indications (such as up, down, left, right, front, back...) in the embodiments of the present invention are only used to explain the relative positional relationship and movement conditions between components in a specific posture. If the specific posture changes, the directional indications will also change accordingly.

[0016] In addition, the descriptions such as "first" and "second" in the present invention are only for descriptive purposes, and cannot be understood as indicating or implying their relative importance or implicitly indicating the quantity of the indicated technical features. Thus, the features defined with "first" and "second" may explicitly or implicitly include at least one of such features. In the description of the present invention, "a plurality" means at least two, such as two, three, etc., unless otherwise specifically defined.

[0017] In the present invention, unless otherwise clearly defined and limited, the terms "connection", "fixation", etc. should be understood in a broad sense. For example, "fixation" may be a fixed connection, a detachable connection, or integrated; it may be a mechanical connection, an electrical connection, a physical connection or a wireless communication connection; it may be directly connected, or indirectly connected through an intermediate medium, and it may be the communication inside two elements or the interaction relationship between two elements, unless otherwise clearly limited. For those of ordinary skill in the art, the specific meanings of the above terms in the present invention can be understood according to specific situations.

[0018] It can be understood that the technical solutions between the various embodiments of the present invention can be combined with each other, but it must be based on the fact that those of ordinary skill in the art can implement it. When the combination of technical solutions is contradictory or cannot be implemented, it should be considered that such a combination of technical solutions does not exist and is not within the protection scope required by the present invention.

[0019] Next, the embodiments of the present invention will be described in detail with reference to the accompanying drawings in the embodiments of the present invention.

[0020] Embodiment 1 As Figure 1 shown, this embodiment discloses a dynamic water depth measurement method, including the following steps: Step 201, arrange a number of sensors in an array on the hydrofoil structure, and collect raw data through each sensor.

[0021] It can be understood that during the high-speed sliding process of the water-air cross-medium robot, it is in a gas-liquid two-phase flow interference environment, and the force states at various parts of the hydrofoil structure change greatly, which will cause the pressure data at the same water depth to change at all times, and it is difficult to avoid the influence of dynamic pressure on pressure measurement. By arranging multiple sensors that can measure pressure in an array on the hydrofoil structure, the sensing data of multiple points can be obtained simultaneously, enabling large-area synchronous sampling of the hydrofoil surface, capturing more comprehensive pressure distribution characteristics on the hydrofoil surface, with strong dynamic adaptability, and being able to better meet the real-time requirements of high-speed sliding.

[0022] In addition, during the water depth measurement process, the sensors will inevitably input noise, which will cause certain errors and reduce the accuracy of water depth measurement. In this embodiment, through the arrangement of multiple sensors, rich data is provided for subsequent accurate calculation, reducing error interference to a certain extent and improving the measurement accuracy.

[0023] Step 202, set a pressure threshold, and perform quantization processing on the raw data according to the pressure threshold to obtain a binary matrix.

[0024] It can be understood that there are significant differences in pressure between water and air. By setting an appropriate pressure threshold, on the one hand, small-amplitude fluctuation signals generated by the sensors due to environmental interference can be eliminated, such as the influence of local water splashing, etc., improving the anti-noise ability. On the other hand, the output of the sensors is quantized into a binary sequence, and the transition point "0-1" of the water-air interface can be clearly identified from the binary sequence, so as to quickly locate the interface position.

[0025] Step 203, based on the binary matrix, use a boundary detection algorithm to determine the initial boundary estimate value in each column of data; then perform arithmetic mean processing on the initial boundary estimate value to obtain the water-air interface estimate value.

[0026] It can be understood that the sensors will generate some systematic errors due to differences in installation positions, manufacturing tolerances, or environmental impacts; and during the high-speed sliding process of the water-air cross-medium robot on the water surface, certain errors and data fluctuations will also be brought about due to attitude adjustments. By independently processing each column of data through a boundary detection algorithm to find the interface transition point "0-1" in that column, the intersection of the possible boundary line intervals in each column, that is, the initial estimation interval, can be obtained to reduce the above errors; then the midpoint of the small interval obtained by the intersection of the initial estimation intervals of each column is taken to obtain a more accurate interface estimate value.

[0027] Step 204: Perform weighted data fusion processing on the estimated interface value to obtain the final measured water depth.

[0028] It can be understood that data filtering is a data processing technology for removing noise and restoring real data. In this embodiment, through Kalman filtering, the estimated interface value is updated and processed in real time, the data of measurement noise is removed, and the optimal estimation of the system state is performed.

[0029] Weighted data fusion makes full use of multi-sensor data resources at different times and spaces, analyzes, synthesizes, dominates and uses the estimated interface values obtained in time series, obtains a consistent interpretation and description of the object to be measured, and then realizes corresponding decisions and estimations, enabling the system to obtain more sufficient information than its individual components.

[0030] In this embodiment, by combining multi-sensors such as IMU and relying on Kalman filtering and multi-sensor weighted fusion technology, real-time and accurate water depth measurement can be performed.

[0031] In the specific implementation process of step 201, mainly the sensors are arranged. The sensors used are sensors that can measure pressure, such as piezoresistive sensors. When collecting data, high-frequency signals are collected by a high-precision high-speed ADC sampling chip and the data is transmitted in a timely manner to meet the real-time requirements.

[0032] The hydrofoil structure includes a hydrofoil bottom plate, a propeller, hydrofoil columns, etc. The sensors can be arranged on the hydrofoil columns and / or the hydrofoil bottom plate, but are mainly arranged on the hydrofoil columns. A number of sensors are arranged on the side surface of the hydrofoil column in an array arrangement; or a number of sensors can be fully arranged along the circumferential direction of the hydrofoil column in an array arrangement.

[0033] When performing the array arrangement, the sensors in m columns in the horizontal direction and n rows in the vertical direction are regarded as an m×n sensor array group. The specific quantities of m and n are determined according to the situation. When only arranging on the side surface of the hydrofoil column, more than one sensor array group can be arranged respectively; when arranging along the circumferential direction of the hydrofoil column, more than one sensor array group can be arranged circumferentially, which is specifically determined according to the requirements. In this embodiment, the sensor array group array is a 3×3 layout. This layout is only for illustrative purposes to clearly explain the technical solution of the present invention and should not be construed as a limitation on the protection scope of the present invention.

[0034] Specifically, in each sensor array group, a mainly adopted scheme is horizontal and vertical dislocation arrangement, such as Figure 2 As shown, the length of the sensor is H and the width is W. It is arranged in m columns in the horizontal direction, and a fixed offset δ is maintained in the horizontal direction between each column. The offset δ satisfies: .

[0035] The heights of the first sensors in adjacent vertical columns are set to be in an arithmetic progression, maintaining a fixed height difference. (In the present invention, several columns maintaining a fixed offset are simply referred to as a group of offset columns), so that the positions of the sensors in each column are staggered. The height difference in the arithmetic progression is determined according to the preset measurement accuracy. Specifically, the height difference satisfies: , where represents the preset measurement accuracy. The height difference is determined by the preset measurement accuracy , which can ensure that after the sensor array is formed, the measurement accuracy meets the system requirements. It should be noted that assuming the overall width of the hydrofoil side is Q, ensuring , the constant m can be directly determined; therefore, the height difference in the arithmetic progression always has the following relationship: .

[0036] n sensors are arranged at equal intervals in each column, and the value of n is designed according to the longitudinal range requirements. The gap interval d between two adjacent sensors is less than or equal to the sensor height H. From this, it can be obtained that the centroid distance between two adjacent sensors in the longitudinal direction is . It should be noted that there may not be a gap interval d between two adjacent sensors in the longitudinal direction, and they are arranged adjacent to each other. At this time, the centroid distance of the sensors is , which is specifically set according to requirements.

[0037] In addition, it can be seen from Figure 2 that starting from to arranged in sequence, and after the last column is fixed, the queue loops back to the first column and continues to be arranged . Set and to also have a height difference of h. Therefore, the centroid distance between two adjacent sensors in the longitudinal direction always has the following relationship: D = m×h.

[0038] Regarding the centroid distance D between two adjacent sensors vertically as a measurement interval, based on the above arrangement, in a sensor array group, the estimation interval of the water surface position can be modeled as having m measurement intervals horizontally and n - 1 measurement intervals vertically. These measurement intervals are arranged horizontally and vertically in a staggered manner, with a stagger distance of h. In each column, the midpoint data of the upper and lower endpoint values of the initial estimation interval is used as the initial junction estimation value. Based on this, it can be known that the initial estimation interval of the water surface position can be modeled as m measurement intervals with a length of D. These initial estimation intervals are arranged in a staggered manner in space, with a stagger distance of h. By solving the intersection of this group of initial estimation intervals, an intersection interval with a length of h can be obtained. Taking the midpoint of the intersection interval as the final interface estimation value can achieve a measurement accuracy of ±h / 2.

[0039] In the specific implementation processes of steps 202 and 203, it is also necessary to preprocess the acquired original data to obtain preprocessed data first. The preprocessing methods include but are not limited to data cleaning and outlier processing. Among them, in the data cleaning process, mature preprocessing algorithms are used to eliminate the influence of noise interference and abnormal data points on subsequent processing. The processed data needs to meet strict input specification requirements, that is, the final pressure data obtained in each column should be monotonically increasing from top to bottom, and only one clear separation point is allowed in each data column.

[0040] Then set the pressure threshold, and perform quantization processing on the preprocessed data according to the pressure threshold to obtain a binary matrix. The expression for the quantization processing is: ; In the formula, represents the quantization value; represents the original data; represents the pressure threshold.

[0041] It can be understood that according to the hydrostatic principle, there are significant differences in pressure between water and air. By combining the actual requirements, the pressure value when the water body submerges the centroid position of the sensor can be set as the pressure threshold ; when the output of the sensor is less than the pressure threshold , the quantization value is marked as 0, indicating that the sensor is above the water surface; when the output of the sensor is greater than or equal to the pressure threshold , the quantization value is marked as 1, indicating that the sensor is below the water surface. Through this threshold comparison mechanism, continuous sensor data can be converted into a discrete binary representation, and its typical feature is shown as a binary sequence pattern such as "00111". It should be noted that the pressure threshold can also be set to other values, not limited to the pressure value when the water body submerges the centroid position of the sensor mentioned in this embodiment.

[0042] In each sensor array group, after the above quantization process, the raw data is transformed into a normalized binary matrix B. This binarization process not only reduces the data dimension and computational overhead but also retains the key feature information of the raw data, providing a standardized data input format for subsequent calculations.

[0043] Based on this binary matrix B, through the boundary detection algorithm, by the quantization values of each column, it is easy to find the "0-1" transition points vertically, so as to quickly locate the interface positions in each column, which are the regions between adjacent sensors corresponding to the transition points. Thus, the initial estimation interval of the water surface position is obtained. By continuously taking the intersection of the initial estimation intervals of each column, after finally obtaining an interval with a length of h and then taking the arithmetic mean of the two end values, the obtained value is the initial interface estimation value in each column of data.

[0044] By calculating all column data, finally, all the initial interface estimation values are processed by arithmetic averaging, and the obtained average value is used as the estimated value of the interface between the water body and the air.

[0045] In the above way, each column of sensors independently executes the single-column measurement algorithm to obtain their respective initial estimation intervals. The final water surface position is determined by taking the intersection of the initial estimation intervals of each column, which can achieve higher measurement accuracy.

[0046] In the specific implementation process of step 204, an IMU sensor and a temperature sensor are assembled on the water-air cross-medium robot.

[0047] The interface estimation value is weighted and fused with the data returned in real time by the IMU sensor, temperature sensor, etc., for attitude compensation and temperature compensation to eliminate the cumulative error, thereby calculating the real-time and accurate water depth data. It should be noted that Kalman filtering processing and multi-sensor data weighted fusion are involved.

[0048] In addition, when performing attitude compensation through the IMU sensor, its theoretical basis lies in the geometric relationship between the spatial position of the sensor array group and the measured value. Since the water-air cross-medium robot may have a non-zero attitude of pitch angle or roll angle, the water depth values measured by the sensor array groups at different positions are different. To solve this problem, it is necessary to establish a compensation model based on the robot attitude sensor through the IMU sensor. In specific implementation, a symmetrically arranged dual-array design scheme can be adopted: the two sensor arrays are installed with the center line of the column as the axis of symmetry, and by collecting the measurement data of the two arrays in real time and calculating their arithmetic mean, the accurate water depth value at the center position of the column can be obtained. This method effectively eliminates the measurement error caused by the change of the robot attitude and improves the spatial accuracy of the water depth data.

[0049] It can be understood that the dynamic water depth measurement method provided by the present invention can effectively suppress the measurement errors caused by local fluctuations on the water surface and reduce the systematic errors by statistically fusing the measurement data of multiple columns of sensors. At the same hardware cost, the measurement accuracy can be increased by m times; at the same time, the modular design facilitates adjusting the array scale and arrangement mode according to actual requirements. During specific implementation, the centroid spacing of the sensors can be optimized in combination with the fluid environment parameters. and the inter-column offset δ to ensure the adaptability of the system and improve the measurement robustness of the system under non-ideal working conditions.

[0050] It is worth noting that the method provided in this embodiment is mainly applied to differential vector robots with hydrofoil structures, such as water-air cross-media robots. However, for other robots with the need for high-precision and high-real-time water depth measurement during water surface gliding, the method proposed by the present invention is also applicable. Any equivalent transformation or parameter optimization based on the core concept of the present invention shall fall within the protection scope of the present invention.

[0051] Although each step in this embodiment Figure 1 is shown in sequence according to the indication of the arrow, these steps are not necessarily executed in the order indicated by the arrow. Unless there is a clear indication in this article, the execution of these steps has no strict order limit, and these steps can be executed in other orders. Moreover, Figure 1 at least a part of the steps may include multiple sub-steps or multiple stages. These sub-steps or stages are not necessarily executed at the same moment, but can be executed at different moments. The execution order of these sub-steps or stages is not necessarily sequential either, but can be executed alternately or in turn with at least a part of other steps or sub-steps or stages of other steps.

[0052] Embodiment 2 Based on the dynamic water depth measurement method in Embodiment 1, this embodiment discloses a dynamic water depth measurement device. As Figure 3 shown, the dynamic water depth measurement device includes: a sensor arrangement module 401, a quantization processing module 402, an interface estimated value calculation module 403, and a water depth measurement module 404, where: The sensor arrangement module 401 is used to set a number of sensors arranged in an array on the hydrofoil structure and collect raw data through each sensor.

[0053] The quantization processing module 402 is used to set a pressure threshold and perform quantization processing on the raw data according to the pressure threshold to obtain a binary matrix.

[0054] The interface estimation value calculation module 403 is configured to determine an initial estimation interval in each column of data based on the binary matrix through a boundary detection algorithm; continuously take intersections based on the initial estimation interval, and perform arithmetic averaging on the final interval to obtain the interface estimation value between the water body and the air.

[0055] The water depth measurement module 404 is configured to perform weighted data fusion processing on the interface estimation value to obtain the final measured water depth.

[0056] In this embodiment, the specific working processes and working principles of the sensor arrangement module 401, the quantization processing module 402, the interface estimation value calculation module 403, and the water depth measurement module 404 are the same as those in the method of Embodiment 1, so they will not be elaborated herein. Each of these unit modules can be implemented in whole or in part by software, hardware, and their combinations. Each unit module can be embedded in the processor of the computer device in hardware form or be independent of it, or be stored in the memory of the computer device in software form, so that the processor can call and execute the operations corresponding to each of the above unit modules.

[0057] Embodiment 3 As Figure 4 shown, a terminal device disclosed in this embodiment includes a transmitter, a receiver, a memory, and a processor. Among them, the transmitter is configured to send instructions and data, the receiver is configured to receive instructions and data, the memory is configured to store computer execution instructions, and the processor is configured to execute the computer execution instructions stored in the memory to implement the method in Embodiment 1 above.

[0058] It should be noted that the above memory can be either independent or integrated with the processor. When the memory is independently provided, the terminal device further includes a bus for connecting the memory and the processor.

[0059] Embodiment 4 This embodiment discloses a computer-readable storage medium in which computer execution instructions are stored. When the processor executes the computer execution instructions, the method in Embodiment 1 above is implemented.

[0060] Those of ordinary skill in the art can understand that all or part of the processes in the methods of the above embodiments can be completed by instructing relevant hardware through a computer program. The computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above methods. Among them, any reference to a memory, storage, database, or other medium used in the embodiments provided in the present application can include non-volatile and / or volatile memories. Non-volatile memory can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), or flash memory. Volatile memory can include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in many forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDR SDRAM), enhanced SDRAM (ESDRAM), synchronous link DRAM (SLDRAM), Rambus direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and Rambus dynamic RAM (RDRAM), etc.

[0061] The technical features of the above embodiments can be combined arbitrarily. For the sake of brevity of description, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, it should be considered as the scope described in this specification.

[0062] The above-described embodiments merely represent several implementation manners of the present invention. The description thereof is relatively specific and detailed, but it should not be construed as a limitation on the scope of the invention. It should be noted that for those of ordinary skill in the art, without departing from the concept of the present invention, several modifications and improvements can still be made, and these all belong to the protection scope of the present invention. Therefore, the protection scope of the present invention should be subject to the appended claims.

Claims

1. A dynamic water depth measurement method, characterized in that, The method includes: arranging a plurality of sensors in an array on a hydrofoil structure, and collecting raw data through each sensor; Setting a pressure threshold, and performing quantization processing on the raw data according to the pressure threshold to obtain a binary matrix; Based on the binary matrix, through a boundary detection algorithm, determining an initial estimation interval in each column of data; continuously taking intersections based on the initial estimation interval, and performing arithmetic mean processing on the final interval to obtain an estimated value of the interface between water and air; Performing weighted data fusion processing on the estimated interface value to obtain a final measured water depth.

2. The dynamic water depth measurement method according to claim 1, wherein The hydrofoil structure includes hydrofoil columns, and a plurality of sensors are arranged on the side surface of the hydrofoil columns in an array arrangement.

3. The dynamic water depth measurement method according to claim 1, wherein The hydrofoil structure includes hydrofoil columns, and a plurality of sensors are arranged along the circumferential direction of the hydrofoil columns in an array arrangement.

4. The dynamic water depth measurement method according to claim 2 or 3, characterized in that The array arrangement is a horizontal and vertical staggered arrangement; when in a horizontal and vertical staggered arrangement, the first sensors in adjacent vertical columns are evenly distributed, and the height difference during even distribution is determined according to a preset measurement accuracy.

5. The dynamic water depth measurement method according to claim 4, wherein The height difference satisfies: , where represents a preset measurement accuracy.

6. The dynamic water depth measurement method according to claim 2 or 3, characterized in that, Setting a pressure threshold, and performing quantization processing on the raw data according to the pressure threshold, with the expression: ； In the formula, represents the quantization value; represents the original data; represents the pressure threshold.

7. The dynamic water depth measurement method according to claim 6, wherein, Continuously taking intersections based on the initial estimation interval, and performing arithmetic mean processing on the final interval to obtain an estimated value of the interface between water and air, including: Continuously taking intersections based on the initial estimation interval to obtain a final first estimation interval, and performing arithmetic mean calculation on the two end values of the first estimation interval to obtain an estimated value of the interface between water and air.

8. A dynamic water depth measurement device, characterized in that, The device includes: A sensor arrangement module, configured to arrange a plurality of sensors in an array on a hydrofoil structure, and collect raw data through each sensor; A quantization processing module, configured to set a pressure threshold, and perform quantization processing on the raw data according to the pressure threshold to obtain a binary matrix; An interface estimated value calculation module, configured to, based on the binary matrix, through a boundary detection algorithm, determine an initial estimation interval in each column of data; continuously take intersections based on the initial estimation interval, and perform arithmetic mean processing on the final interval to obtain an estimated value of the interface between water and air; A water depth measurement module, configured to perform weighted data fusion processing on the estimated interface value to obtain a final measured water depth.

9. A computer device, comprising a memory and a processor, the memory storing a computer program, characterized in that, When the processor executes the computer program, the steps of the dynamic water depth measurement method according to any one of claims 1 to 7 are implemented.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, the steps of the dynamic water depth measurement method according to any one of claims 1 to 7 are implemented.

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