Integrated adcp data acquisition system and method thereof

Abstract

This invention relates to the field of hydrological measurement equipment technology, and discloses an integrated ADCP data acquisition system and method. The system includes a data acquisition terminal, a mobile ADCP, a cloud server, a shore-based receiver, and a client. The data acquisition terminal includes a waterproof housing. The method includes: Step S1: Before the ADCP performs acoustic acquisition, based on a preset flow field expression target, a set of acoustic flow field reference coordinate system frameworks is constructed to define the water flow field in the time and depth dimensions. This system and method avoids data loss due to network issues through a multi-mode communication and packet loss prevention storage collaborative mechanism. Simultaneously, by constructing a spatiotemporal two-dimensional acoustic flow field reference coordinate system and allowing the device to adaptively improve, the measurement accuracy and reliability in complex environments can be enhanced. Finally, by using a dimensionality reduction calculation model, the device can be converted into a high-precision current meter, achieving an integrated single-device multi-purpose effect.

Description

Technical Field

[0001] This invention relates to the field of hydrological measurement equipment technology, specifically to an integrated ADCP data acquisition system and method. Background Technology

[0002] Acoustic Doppler Current Profiler (ADCP) is a hydrological observation device based on the Doppler effect, widely used for measuring flow velocity, direction, and underwater topography in rivers, lakes, and oceans. Traditional mobile ADCPs are typically mounted on manned survey vessels or unmanned surface vessels (USVs) for cross-sectional navigation during testing operations, addressing the limitation of traditional single-point current meters in acquiring large-scale water profile data. To obtain three-dimensional flow field data with absolute geographic coordinates and precise heading, existing mobile ADCPs usually require a series of external auxiliary devices. Specifically, their typical operating mode involves the system connecting a dedicated GNSS positioning device, compass, and an external battery pack for sustained navigation via a dedicated data cable. Simultaneously, using short-range wireless transmission technologies such as wired cables or Bluetooth, the acquired acoustic data is transmitted in real-time to an accompanying operating computer or dedicated data acquisition terminal. Finally, the data is collected and processed by the accompanying measurement and control software provided by each manufacturer. Although the aforementioned traditional mobile ADCP system can achieve basic measurements of hydrological cross sections, in actual field operations and complex application scenarios, this working mode, which relies on piecing together multiple devices, has gradually revealed obvious limitations. Currently, the technology typically uses onboard data acquisition terminals to integrate and use the data in a unified manner.

[0003] However, common data acquisition terminals in practical applications suffer from the following drawbacks: First, traditional ADCP terminals require data transmission with onshore equipment via radio waves or cables, limiting their effectiveness due to geographical constraints. Furthermore, some devices capable of network transmission rely on the strength of the network signal in the measurement environment, leading to network connectivity issues and data loss in areas with poor signal strength. Second, ADCP typically employs pre-set fixed acquisition parameters and a single acoustic emission strategy to measure flow velocity and direction. This approach lacks adaptive adjustment capabilities for changes in the flow field over time and depth. When the water flow field fluctuates over time or exhibits significant differences at different depths, a uniform acoustic acquisition mode struggles to simultaneously meet the flow field representation needs of various regions. This can result in insufficient local information, unstable echo quality, or decreased data consistency, affecting the overall reliability and stability of the acquisition results. Consequently, it becomes difficult to obtain accurate and reliable characterizations of complex flow fields, leading to insufficient accuracy and reliability in the acquisition results. Third, many measurement stations still need to be used in conjunction with traditional equipment for flow velocity testing. The process of collecting water flow data has the drawback that multiple sets of equipment are required to complete the measurement and application, and the data is difficult to provide to the supporting stations for direct use. Summary of the Invention

[0004] The present invention aims to address the shortcomings of the prior art by providing an integrated ADCP data acquisition system and method, which addresses the technical problems of existing systems such as easy loss of data transmission, difficulty in taking into account flow field changes under different time and depth conditions, insufficient accuracy and reliability of acquisition results, and poor applicability due to the difficulty of directly applying the acquired data to the site.

[0005] To solve the above-mentioned technical problems, the technical solution of the present invention is as follows: An integrated ADCP data acquisition system, characterized in that it comprises: An integrated ADCP data acquisition system includes a data acquisition terminal, a mobile ADCP, a cloud server, a shore-based receiver, and a client. The data acquisition terminal includes a waterproof housing and a main control module, a multi-mode communication module, a positioning and orientation module, a storage module, and a power supply module disposed inside the waterproof housing. The main control module is electrically connected to each of the above modules. An ADCP cable port is provided on the waterproof housing, and the main control module is electrically connected to the mobile ADCP externally through the ADCP cable port. The main control module is used to control the power supply module to provide power to the mobile ADCP and receive the underlying echo data, synchronously acquire the position and heading information of the positioning and orientation module, process it, and then send it to the cloud server or the shore-based receiver via the multi-mode communication module. The client communicates with the cloud server, the shore-based receiver, and the data acquisition terminal to exchange data.

[0006] Furthermore, the multi-mode communication module includes a network unit and a radio station unit; the main control module communicates bidirectionally with the cloud server via the network unit using the MQTT protocol through the 5G / 4G network; the main control module establishes a long-distance radio station transparent transmission connection with the shore-based receiver through the radio station unit; the client includes a PC client and / or a mobile application, and the client includes a multi-link communication architecture: connecting to the shore-based receiver via a USB or Bluetooth interface to obtain radio transparent transmission data, directly communicating with the data acquisition terminal via the 5G / 4G network, and simultaneously establishing communication with the cloud server via the Internet.

[0007] Furthermore, the main control module has a built-in communication link detection program. During the data acquisition process, it prioritizes sending data to the cloud server through the network unit, and then transmits it to the client through the cloud server. During the data acquisition process, the data is synchronously stored in the storage module. When the network signal is lost, it can choose to transmit the data to the shore receiver by connecting to the radio unit, and then transmit it to the client through the shore receiver via wired or Bluetooth. While sending real-time data, it also compensates for and resumes the transmission of historical network outage data in the storage module.

[0008] Furthermore, the positioning and orientation module is used to receive satellite signals for RTK positioning and to acquire heading information; the main control module synchronously acquires the RTK positioning information and heading information output by the positioning and orientation module, combines them with the underlying echo data of the mobile ADCP, performs spatial coordinate alignment and error elimination, and extracts flow velocity data and outputs RTK positioning data based on the aligned coordinates, so as to simultaneously realize the measurement of water flow velocity and direction and underwater topography measurement.

[0009] Furthermore, the waterproof housing has a power button, status indicator lights, and a power display on its panel, and a charging port, a radio antenna port, and a heading antenna port on the other side; the data acquisition terminal has a connector on its exterior, and the data acquisition terminal is fixed to an external bracket or float as a hydrological telemetry terminal through the connector; the storage module is equipped with a local memory card, and the power module is equipped with a battery pack for providing operating power.

[0010] Furthermore, the main control module supports a timed sleep and wake-up mechanism. After acquiring the measurement time and preheating power supply parameters, it wakes up the power module at the set time to preheat the mobile ADCP and execute the fixed-point current meter measurement mode. When executing the fixed-point current meter measurement mode, the main control module performs average segmented measurements on multiple points in the vertical direction according to the number of measurement points set by the user. It extracts and interpolates to calculate the single-point flow velocity value at the depth of multiple points below the water surface, and uses the corresponding formula to obtain and output the single-point vertical average flow velocity. After the measurement is completed, it automatically disconnects the power supply to the external device and forwards the data, realizing remote cluster control of multiple cloud flow measurement terminals.

[0011] Furthermore, the main control module has a built-in acoustic acquisition program based on component pool adaptive matching; when receiving the underlying echo data acquired by the mobile ADCP, the main control module dynamically generates and combines multiple acoustic segment components according to the expression requirements of the water flow field in the time and depth dimensions to adjust the energy and direction disturbance of acoustic emission in real time, and performs weighted fusion based on the echo response characteristics to update the weight state of each component.

[0012] An integrated ADCP data acquisition method, applied to an integrated ADCP data acquisition system, the method comprising: Step S1: Before ADCP performs acoustic acquisition, based on the preset flow field expression target, construct a set of acoustic flow field reference coordinate system frameworks to limit the water flow field in the time and depth dimensions; Step S2: Based on the acoustic flow field reference coordinate system framework, combine acoustic emission energy, emission direction disturbance and echo events into multiple acoustic segment components, and assign corresponding reference coordinate indices to establish an acoustic segment component pool; Step S3: During the acoustic acquisition process, based on the flow field expression requirements of different coordinate regions within the acoustic flow field reference coordinate system frame, multiple acoustic segment components are selected from the acoustic segment component pool and arranged in a preset order to perform acoustic transmission and reception. Step S4: For each executed acoustic segment component, update its state attributes based on the corresponding echo response characteristics. The state attributes include component confidence, information density, or spatial consistency index. Step S5: Generate acquisition results by performing correlation analysis between the acoustic segment components with updated state attributes and the coordinate index of the acoustic flow field reference coordinate system frame.

[0013] Furthermore, step S3 specifically includes: introducing expression consistency constraints to jointly divide the time and depth dimensions to form multiple flow field expression regions; generating a set of regional expression requirement parameters based on the expression consistency constraints, and mapping the requirement parameters for sensitivity to flow field changes to the emission energy envelope characteristics and echo time window width, and mapping the requirement parameters for vertical resolution consistency to the emission direction disturbance amplitude and directional distribution pattern; performing primary constraint screening based on the mapping relationship to establish a candidate subset of components, and introducing state attributes as secondary constraints for multi-dimensional matching screening and evaluation; classifying the acoustic segment components into coverage roles based on differences, the roles including basic coverage components and enhanced coverage components; selecting at least one of the above components for the same flow field expression region to construct an acoustic segment component combination that satisfies the constraints of spatial coverage integrity and information complementarity, and performing acoustic transmission and reception after determining the execution order based on the roles and consistency evaluation results.

[0014] Further, step S4 specifically includes: extracting the echo response feature set bound to the acoustic segment components, and using the echo energy attenuation curve to update the component credibility, the effective scattering layer distribution feature to update the information density, and the echo phase stability and temporal consistency feature to update the spatial consistency index; in this process, a coordinate index is introduced to perform coordinate association weighted update, and when the component credibility or spatial consistency index is lower than the preset stability threshold for two consecutive periods, it is marked as a low-stability component and weight attenuation or frequency restriction is applied; step S5 specifically includes: performing coordinate aggregation of the acoustic segment components participating in the acquisition according to the time coordinate and depth coordinate; for each coordinate-associated component set, generating a comprehensive weight parameter characterizing the reliability of the flow field expression based on the component credibility, information density, and spatial consistency index of each component; based on the comprehensive weight parameter, performing weighted fusion processing on the echo observation results formed by multiple acoustic segment components in the corresponding coordinate region to generate the acquisition results.

[0015] Compared with the prior art, the beneficial effects of the technical solution of the present invention are: To address the shortcomings of traditional mobile ADCPs that are prone to data loss due to radio signal loss, the system employs a multi-mode communication and packet loss prevention storage collaborative mechanism. When facing public network blind spots in remote hydrological areas, it can use the network in conjunction with the radio station to transmit data transparently and simultaneously back it up to the local storage module. Once the network is restored or the system approaches the shore, it performs breakpoint resume compensation, avoiding the problem of three-dimensional flow field data loss due to signal fluctuations during water operations and ensuring the integrity of the data link. Addressing the fundamental technical bottleneck of traditional ADCP (Advanced Digital Acoustic Processing) systems, which rely on fixed acquisition parameters and a single acoustic strategy and struggle to handle multidimensional changes in water depth and time, this invention constructs a spatiotemporal two-dimensional acoustic flow field reference coordinate system. This system dynamically schedules and combines acoustic segments with different emission energies, directional perturbations, and time windows based on the flow field gradient and representation requirements of different regions. Furthermore, it uses echo characteristics to update the reliability, information density, and other weights of the components in real time for weighted fusion calculations. This method endows ADCP with adaptive environmental perception capabilities for complex flow fields, providing high-precision and highly reliable full-depth flow field acquisition results. To address the shortcomings of existing mobile navigation terminals that are difficult to directly apply to fixed-station flow measurement, this invention incorporates a data dimensionality reduction model in a current meter mode based on the generated three-dimensional data. It can automatically extract single-point flow velocities at different underwater depths and, based on user-defined vertical multi-point measurements, directly output the average vertical flow velocity at each single point, transforming the mobile device into a high-precision traditional fixed-point current meter. Attached Figure Description

[0016] To more clearly illustrate the technical solution of the present invention, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0017] Figure 1 This is a schematic diagram of the system structure of the present invention.

[0018] Figure 2 This is a schematic diagram of the data acquisition terminal structure of the present invention.

[0019] Figure 3 This is a schematic diagram of the data acquisition terminal circuit of the present invention.

[0020] Figure 4 This is a schematic diagram of the method flow of the present invention.

[0021] Figure 5 This is a schematic diagram of a specific embodiment of the present invention.

[0022] The reference numerals in the attached diagram are as follows: 100-Data acquisition terminal; 110-Waterproof housing; 111-Power button; 112-Status indicator light; 113-Power display screen; 114-ADCP cable port; 115-Charging port; 116-Radio antenna port; 117-Heading antenna port; 120-Main control module; 130-Multimode communication module; 131-Network unit; 132-Radio unit; 140-Positioning and orientation module; 150-Storage module; 160-Power supply module; 170-Connector; 200-Mobile ADCP; 300-Cloud server; 400-Shore receiver; 500-Client; 610-Coordinate system framework construction module; 620-Component pool establishment module; 630-Transmit and receive module; 640-Update module; 650-Analysis module. Detailed Implementation

[0023] To make the objectives, technical solutions, and advantages of the embodiments of this application clearer, the technical solutions of this application will be clearly and completely described below with reference to the accompanying drawings of the embodiments of this application. Obviously, the described embodiments are only some, not all, of the embodiments of this application. All other embodiments obtained by those skilled in the art based on the described embodiments without creative effort are within the scope of protection of this application.

[0024] Unless otherwise defined, the technical or scientific terms used in this application shall have the ordinary meaning understood by one of ordinary skill in the art to which this application pertains. The terms "first," "second," and similar terms used in this application do not indicate any order, quantity, or importance, but are merely used to distinguish different components. Terms such as "comprising" or "including" mean that the element or object preceding the word encompasses the elements or objects listed following the word and their equivalents, without excluding other elements or objects. Terms such as "connected" or "linked" are not limited to physical or mechanical connections, but can include electrical connections, whether direct or indirect. Terms such as "upper," "lower," "left," and "right" are used only to indicate relative positional relationships; when the absolute position of the described object changes, the relative positional relationship may also change accordingly.

[0025] The present application will now be described in detail with reference to the accompanying drawings and specific embodiments.

[0026] Example 1: Hardware architecture of an integrated ADCP data acquisition system.

[0027] like Figure 1-2As shown, traditional mobile ADCPs often require heavy external batteries, complex communication radios, positioning and orientation equipment, and operating computers when conducting hydrological surveys in the field. This results in complicated on-site cabling and makes the equipment prone to damage due to wiring errors or water ingress.

[0028] To address the aforementioned pain points, this embodiment 1 proposes an integrated ADCP data acquisition system, including a data acquisition terminal 100, a mobile ADCP 200, a cloud server 300, a shore-based receiver 400, and a client 500. The data acquisition terminal 100 includes a waterproof housing 110, and a main control module 120, a multi-mode communication module 130, a positioning and orientation module 140, a storage module 150, and a power module 160 disposed inside the waterproof housing 110. The main control module 120 is electrically connected to each of the above modules. An ADCP circuit is provided on the waterproof housing 110. The main control module 120 is electrically connected to the external mobile ADCP 200 via the ADCP cable port 114. The main control module 120 is used to control the power module 160 to provide power to the mobile ADCP 200 and receive the underlying echo data. It synchronously acquires the position and heading information of the positioning and orientation module 140, processes it, and then sends it to the cloud server 300 or the shore receiver 400 via the multi-mode communication module 130. The client 500 communicates with the cloud server 300, the shore receiver 400, and the data acquisition terminal 100 to perform data interaction.

[0029] In order to meet the stringent requirements of the hydrological environment and provide a solid physical support for the system, the mechanical structure of the data acquisition terminal 100 in this embodiment has been specially designed.

[0030] In terms of cavity structure, the interior of the waterproof housing 110 is divided into an independent battery cavity and a main control cavity by a sealed partition. The main control module 120 achieves passive heat dissipation by physically contacting the metal heat dissipation area on the inner wall of the waterproof housing 110 through a thermally conductive silicone patch. The network antenna of the internal multimode communication module 130 and the radio frequency antenna of the positioning and orientation module 140 are arranged diagonally to maximize physical isolation from electromagnetic interference.

[0031] In terms of external assembly structure, the connector 170 of this system preferably includes a clamp base and a multi-position angle adjustment bracket, and a flexible damping shock-absorbing pad is sandwiched on the connection surface between the connector 170 and the waterproof housing 110 to eliminate the flow measurement vibration error caused by water flow impact. The heavier power module 160 is fixed to the bottom area of ​​the waterproof housing 110 to lower the overall center of gravity of the equipment. In addition, the ADCP cable port 114 adopts an aviation socket with a foolproof positioning pin and a threaded locking waterproof cover. The above optimization of hardware structure improves the protection capability of this system in an unattended outdoor state.

[0032] Furthermore, the positioning and orientation module 140 is used to receive satellite signals for RTK positioning and to acquire heading information; the main control module 120 synchronously acquires the RTK positioning information and heading information output by the positioning and orientation module 140, combines it with the underlying echo data of the mobile ADCP200, performs spatial coordinate alignment and error elimination, and extracts flow velocity data and outputs RTK positioning data based on the aligned coordinates, so as to simultaneously realize the measurement of water flow velocity and direction and underwater topography measurement.

[0033] Furthermore, the waterproof housing 110 has a power button 111, a status indicator light 112, and a power display screen 113 on its panel, and a charging port 115, a radio antenna port 116, and a heading antenna port 117 on the other side; the data acquisition terminal 100 has a connector 170 on its exterior, and the data acquisition terminal 100 is fixed to an external bracket or float as a hydrological telemetry terminal through the connector 170; the storage module 150 is equipped with a local memory card, and the power module 160 is equipped with a battery pack for providing operating power.

[0034] Example 2: Preventing data from being affected by poor network conditions and packet loss.

[0035] like Figure 3 As shown, since hydrological surveys are often conducted in remote river sections, public network signals frequently have blind spots. This embodiment further illustrates the data coordination and packet loss prevention logic of the main control module 120.

[0036] Furthermore, the multi-mode communication module 130 includes a network unit 131 and a radio unit 132; the main control module 120 communicates bidirectionally with the cloud server 300 via the network unit 131 using the MQTT protocol over a 5G / 4G network; the main control module 120 establishes a long-distance radio transmission connection with the shore receiver 400 via the radio unit 132; the client 500 includes a PC client and / or a mobile application (APP), and the client 500 includes a multi-link communication architecture: it connects to the shore receiver 400 via a USB or Bluetooth interface to obtain radio transmission data, communicates directly with the data acquisition terminal 100 via a 5G / 4G network, and simultaneously establishes communication with the cloud server 300 via the Internet.

[0037] Furthermore, the main control module 120 has a built-in communication link detection program. During the data acquisition process, it prioritizes sending data to the cloud server 300 through the network unit 131. During the data acquisition process, the data is synchronously stored in the storage module 150. When the network signal is lost, it can choose to transmit the data to the shore receiver 400 by connecting to the radio unit 132, and transmit it to the client 500 through the shore receiver 400 via wired or Bluetooth. When the network is detected to be restored, it compensates for and resumes the transmission of historical network outage data in the storage module 150 while sending real-time data.

[0038] On the worker's client 500, the user can use a PC client and a mobile application APP to directly connect to the shore receiver 400 and the data acquisition terminal 100 via Bluetooth or network, or receive signals via the network through the cloud server 300 port, and use this method to remotely receive data and remotely control the shore receiver 400. When a network signal loss is detected, the main control module 120 automatically switches to the radio unit 132 to transmit data to the receiver 400 on shore, ensuring uninterrupted connection at the on-site command center. Simultaneously, the main control module 120 continuously writes timestamped collected data into the storage module 150 for local protection. The storage module 150 preferably includes both a high-speed flash memory unit and a local memory card for dual backup. When the public network is restored, the main control module 120 automatically retrieves historical network outage data from the storage module 150 for compensatory transmission while sending real-time data, ensuring the integrity of the flow field data acquired by the cloud server 300.

[0039] Example 3: Acoustic data acquisition and calibration based on component pool.

[0040] like Figure 4 The present invention aims to address the technical problem in existing ADCP data acquisition processes that make it difficult to simultaneously account for flow field changes under different time and depth conditions, resulting in insufficient reliability of the acquisition results.

[0041] In this embodiment, the main control module 120 incorporates a component pool-based adaptive matching acquisition algorithm. When receiving the underlying echo data acquired by the mobile ADCP200, the main control module 120 dynamically generates and combines multiple acoustic segment components according to the expression requirements of the water flow field in the time and depth dimensions to adjust the energy and direction perturbation of acoustic emission in real time. It also updates the weight state of each component based on the echo response characteristics for weighted fusion, which is used to control the external mobile ADCP200 to perform extremely precise acoustic acquisition operations. The method specifically includes: Step S1: Before ADCP performs acoustic acquisition, based on the preset flow field expression target, construct a set of acoustic flow field reference coordinate system frameworks to limit the water flow field in the time and depth dimensions; In this embodiment, before the mobile ADCP200 performs acoustic data acquisition, a preset flow field representation target is first determined based on the measurement task requirements. This target clarifies the time range, temporal resolution, and vertical depth coverage and resolution requirements of the water flow field. For example, the measurement duration is set to 30 minutes, the acquisition time interval to 1 second, and the 10-meter deep water body is divided into 0.5-meter depth intervals, thus ensuring that flow field data needs to be acquired at different times and depths. After determining the flow field representation target, the entire measurement cycle is divided into time intervals to form a continuous time-dimensional coordinate axis, and the vertical structure of the water body is divided into depth intervals to form a continuous depth-dimensional coordinate axis.

[0042] After dividing the time and depth dimensions, the time and depth coordinate axes are combined and mapped to ensure that each time position and each depth position corresponds to a unique coordinate index, thereby constructing an acoustic flow field reference coordinate system framework covering the entire measurement cycle and the full water depth range. This framework uniformly defines the positional relationships of the water flow field in the time and depth dimensions, enabling subsequent acoustic emission, echo reception, and data processing to be correlated and compared based on a consistent spatiotemporal reference.

[0043] Step S2: Based on the acoustic flow field reference coordinate system framework, combine acoustic emission energy, emission direction disturbance and echo events into multiple acoustic segment components, and assign corresponding reference coordinate indices to establish an acoustic segment component pool; In this embodiment, the acoustic acquisition process of the mobile ADCP200 is standardized and decomposed based on the acoustic flow field reference coordinate system framework, clearly breaking down a complete acoustic acquisition into quantifiable and reproducible components. Specifically, in each acoustic acquisition, the acoustic emission energy parameters are first determined. For example, when measuring a water depth of 0-5 meters, the acoustic emission energy is set to a fixed power value P1, and when measuring a water depth of 5-10 meters, the acoustic emission energy is set to a fixed power value P2 to ensure that the echo signal has sufficient amplitude within the corresponding depth range. At the same time, the emission direction disturbance parameters are determined. For example, with the nominal emission direction of the mobile ADCP200 as the center, the emission direction is set to emit at three fixed angles of -1°, 0°, and +1° to cover adjacent spatial directions. The echo events formed under the above acoustic emission conditions are recorded. The echo events include the complete process of the acoustic signal propagating in the water after emission, scattering with suspended particles, and being received within a preset echo time range.

[0044] After determining the above parameters, a set of determined acoustic emission energy parameters, a corresponding set of emission direction disturbance parameters, and the echo events formed under these conditions are combined to form an acoustic segment component. Each acoustic segment component corresponds to a fixed and specific acoustic emission and echo reception configuration, such as an acoustic acquisition process completed under a certain fixed emission power and a certain fixed emission direction.

[0045] After the acoustic segment components are formed, a corresponding reference system coordinate index is assigned to each acoustic segment component based on the time and depth dimensions already defined in the acoustic flow field reference coordinate system framework. For example, the acoustic segment component is associated with a specific acquisition time and a specific depth range, thus ensuring a one-to-one correspondence between the acoustic segment component and the water flow field in the time and depth dimensions. Finally, all acoustic segment components and their reference system coordinate indices are centrally stored and managed to establish an acoustic segment component pool.

[0046] Step S3: During the acoustic acquisition process, based on the flow field expression requirements of different coordinate regions within the acoustic flow field reference coordinate system frame, select and arrange multiple acoustic segment components from the acoustic segment component pool in a preset order to perform acoustic transmission and reception. In this embodiment, during acoustic acquisition, based on the flow field expression requirements of different coordinate regions within the acoustic flow field reference coordinate system, expression consistency constraints are introduced to jointly divide the time and depth dimensions, forming multiple flow field expression regions. The corresponding flow field expression requirements are determined based on the flow field change gradient distribution and historical echo stability distribution within each flow field expression region. For each flow field expression region, a region expression requirement parameter set is generated based on the flow field expression requirements and the expression consistency constraints. This parameter set characterizes the specific requirements of the flow field expression region for flow field change sensitivity, vertical resolution consistency, and temporal continuous coverage. Then, based on the region expression requirement parameter set, multi-dimensional matching and filtering are performed on the acoustic fragment components in the acoustic fragment component pool. Based on the multi-dimensional matching and filtering results, acoustic fragment component combinations are configured and arranged in a preset order to perform acoustic transmission and reception processing. This achieves the selection and arrangement of multiple acoustic fragment components from the acoustic fragment component pool in a preset order to perform acoustic transmission and reception based on the flow field expression requirements of different coordinate regions within the acoustic flow field reference coordinate system.

[0047] Furthermore, in the method provided in the application embodiments, based on the flow field expression requirements of different coordinate regions within the acoustic flow field reference coordinate system frame, multiple acoustic segment components are selected from the acoustic segment component pool and arranged in a preset order to perform acoustic transmission and reception, and the method further includes: Within the acoustic flow field reference coordinate system framework, an expression consistency constraint is introduced to jointly divide the time and depth dimensions, forming multiple flow field expression regions. Each flow field expression region is determined by the flow field change gradient distribution and historical echo stability distribution within the corresponding region. For each flow field expression region, a set of region expression requirement parameters is generated based on the expression consistency constraint. This set includes requirements for sensitivity to flow field changes, vertical resolution consistency, and temporal continuity coverage. Based on the region expression requirement parameter set, multi-dimensional matching and filtering are performed on the acoustic fragment components in the acoustic fragment component pool. After configuring the acoustic fragment component combinations according to the multi-dimensional matching and filtering results and setting the execution order, acoustic transmission and reception processing are performed.

[0048] In this embodiment, during the acoustic acquisition process, a consistency constraint is first introduced into the acoustic flow field reference coordinate system to jointly divide the time and depth dimensions. Specifically, the time interval and depth interval are first determined, for example, the time interval is set to 1 second and the depth interval is set to 0.5 meters. Then, at each time position and each depth position, the flow velocity data and flow direction data at the corresponding position are read. The flow field change gradient distribution is then calculated. This flow field change gradient distribution is obtained by the flow velocity difference between adjacent time positions and the flow velocity difference between adjacent depth positions. For example, if the flow velocity at the same depth at two adjacent time points is 1.2 m / s and 1.3 m / s respectively, the flow velocity difference in the time direction is 0.1 m / s. If the flow velocity at two adjacent depth positions at the same time point is 1.2 m / s and 1.0 m / s respectively, the flow velocity difference in the depth direction is 0.2 m / s. All time direction differences and depth direction differences in the same region are statistically analyzed to form the flow field change gradient distribution of that region. Simultaneously, the historical echo stability distribution is calculated. This distribution is obtained by statistically analyzing the historical echo amplitudes at the same time and depth locations. For example, if the echo amplitudes of 10 consecutive acquisitions are 100, 102, 98, 101, 99, 100, 101, 99, 100, and 102, the difference between the maximum and minimum values ​​is calculated to be 4. The average of these 10 values ​​is then calculated to be 100.3. When the difference between the maximum and minimum values ​​does not exceed one-tenth of the average value, the echo at that location is considered to be in a stable state. Finally, under the constraint of consistency, the flow field change gradient distribution at corresponding locations in the time and depth dimensions is compared one by one with the historical echo stability distribution. When the difference in flow field change gradients between adjacent time or depth locations does not exceed a preset change threshold, and the fluctuation range of the corresponding historical echo amplitude is within a preset stability range, the time and depth locations are merged into the same flow field expression region, thus forming multiple flow field expression regions within the acoustic flow field reference coordinate system framework.

[0049] Next, for each flow field expression region, a set of region expression requirement parameters is generated based on expression consistency constraints. Specifically, based on the statistically obtained flow field change gradient distribution within the flow field expression region, the required parameters for sensitivity to flow field changes are determined. When the statistical average of the velocity difference in the time direction is not less than 0.1 m / s, or the statistical average of the velocity difference in the depth direction is not less than 0.2 m / s, the acoustic acquisition configuration corresponding to the flow field expression region needs to set the acoustic emission energy to the calibration energy value corresponding to the maximum depth of the target coverage, set the emission direction perturbation to cover multiple preset fixed direction angles, and maintain the acquisition time interval at 1 second to ensure real-time tracking of velocity changes. When the above difference is lower than the corresponding threshold, the acoustic emission energy is set to the calibration energy value corresponding to the average depth of the target coverage, the emission direction perturbation is set to the reference direction, and the acquisition time interval is maintained at 1 second. Based on the statistical results of the velocity differences between adjacent depth positions within the flow field representation area, the required parameters for vertical resolution consistency are determined. For example, when the statistical average velocity difference between adjacent 0.5-meter depth positions is not less than 0.15 meters per second, acoustic acquisition is required to maintain continuous depth coverage of 0.5 meters within this depth range; when the difference is less than 0.15 meters per second, the predetermined depth division is allowed to remain unchanged. Based on the acquisition requirements of the flow field representation area in the time direction, the required parameters for temporal continuous coverage are determined. The temporal continuous coverage requirement parameters stipulate that an effective acoustic acquisition must be completed every 1 second within the flow field representation area. The required parameters for sensitivity to flow field changes, vertical resolution consistency, and temporal continuous coverage are combined to form a set of regional representation requirement parameters, which is used to fully describe the flow field representation requirements of the flow field representation area.

[0050] Subsequently, based on the regional expression requirement parameter set, multi-dimensional matching and screening are performed on the acoustic fragment components in the acoustic fragment component pool. In this process, the regional expression requirement parameter set is first mapped to the physical attribute space of the acoustic fragment components, so that the requirement parameter for flow field change sensitivity corresponds to the emission energy envelope characteristics and echo time window width of the acoustic fragment component, and the requirement parameter for vertical resolution consistency corresponds to the emission direction perturbation amplitude and directional distribution pattern of the acoustic fragment component. After mapping, primary constraint screening is performed on the acoustic fragment components in the acoustic fragment component pool according to the mapping relationship, forming a candidate subset of components that meet the basic requirements of the regional expression requirement parameter set. Then, the state attributes of the acoustic fragment components are introduced into the candidate subset as secondary screening constraints. Based on the credibility evolution trend, information density distribution, and spatial consistency index of each acoustic fragment component, the candidate subset is screened to establish an acoustic fragment component set. Finally, a joint constraint evaluation of emission energy coverage, directional perturbation distribution, and echo time window overlap is performed on the acoustic fragment component set to form the multi-dimensional matching and screening results.

[0051] Finally, based on the multi-dimensional matching and filtering results, the acoustic segment component combinations are configured, and the execution order is set before acoustic transmission and reception processing is performed. During this process, based on the differences in transmission energy coverage, directional perturbation distribution, and echo time window width among the acoustic segment components in the multi-dimensional matching and filtering results, the acoustic segment components are assigned coverage roles, forming basic coverage components for establishing the acoustic interpretation boundary of the flow field expression region and enhanced coverage components for refining the internal flow field structure of the acoustic interpretation boundary. Subsequently, for the same flow field expression region, at least one acoustic segment component is selected from both the basic and enhanced coverage components to construct an acoustic segment component combination that simultaneously satisfies the spatial coverage integrity constraint and the information complementarity constraint of the flow field expression region. Finally, based on the coverage role of each acoustic segment component in the acoustic segment component combination and its consistency evaluation results in the multi-dimensional matching and filtering results, the execution order of the acoustic segment components is determined, and acoustic transmission and reception processing are performed sequentially according to the execution order, thereby achieving ordered acoustic acquisition for the flow field expression region.

[0052] Furthermore, in the method provided in the application embodiments, performing multi-dimensional matching and filtering of acoustic fragment components in the acoustic fragment component pool based on the region expression requirement parameter set further includes: The set of regional representation requirements parameters is mapped to the physical attribute space of acoustic segment components. Specifically, the requirement parameter for sensitivity to flow field changes is mapped to the emission energy envelope characteristics and echo time window width of the acoustic segment component, while the requirement parameter for vertical resolution consistency is mapped to the emission direction perturbation amplitude and directional distribution pattern of the acoustic segment component. Based on the mapping relationship, the acoustic segments in the acoustic segment component pool are subjected to primary constraint screening to establish a component candidate subset. In the component candidate subset, the state attributes of the acoustic segment components are introduced as secondary screening constraints. Based on the credibility evolution trend, information density distribution, and spatial consistency index of each acoustic segment component, an acoustic segment component set is established. The joint constraint evaluation of the emission energy coverage, directional perturbation distribution, and echo time window overlap of the acoustic segment component set is performed to establish a multidimensional matching screening result.

[0053] In this embodiment, the set of regional representation requirements parameters is first mapped to the physical attribute space of the acoustic segment components. In this process, the requirements parameters for sensitivity to flow field changes are first given as the target measurement depth range, the target time sampling interval, and the effective depth range of the target echo. Then, the target depth range is converted into the echo time window width. Taking the sound velocity in water as 1500 m / s, the acoustic signal round-trip propagation time = 2 × target depth / sound velocity. For example, if the target depth is 10 m, then the round-trip propagation time = 2 × 10 / 1500 ≈ 0.0133 s. Based on this, the start and end boundaries of the echo time window width are calculated. The redundancy time is taken as 20% of the round-trip propagation time, i.e., 0.0133 × 0.20 ≈ 0.0027 s. The start time = 0.0133 - 0.0027 ≈ 0.0106 s, and the end time = 0.0133 + 0.0027 ≈ 0.0160 s. Thus, the requirements parameters for sensitivity to flow field changes are mapped to the echo time window width. The range is 0.0106s to 0.0160s. Simultaneously, the sensitivity parameters for flow field changes are mapped to the emission energy envelope characteristics. Propagation loss is proportional to distance, with 1m corresponding to 1 energy unit. Therefore, a target depth of 10m corresponds to a propagation loss of 10 energy units. A safety margin of 30% of the propagation loss is taken, i.e., 10 × 0.30 = 3 energy units. The energy value corresponding to the emission energy envelope characteristics is 10 + 3 = 13 energy units. The vertical resolution consistency requirements are mapped to the emission direction disturbance amplitude and directional distribution pattern. The depth division interval is given as 0.5m, the beam coverage cone angle as 20°, the emission direction disturbance amplitude as 10% of the beam coverage cone angle (±2°), and the directional distribution pattern as a discrete set of directions centered at 0° with 1° increments (-2°, -1°, 0°, 1°, 2°).

[0054] Next, based on the mapping relationship, a primary constraint screening is performed on the acoustic fragment components in the acoustic fragment component pool. In this process, for each acoustic fragment component, its emitted energy envelope characteristics, echo time window width, emitted direction perturbation amplitude, and directional distribution pattern are read. For the echo time window width, a range inclusion judgment is performed, requiring the echo time window width of the acoustic fragment component to completely cover 0.0106s~0.0160s; if it covers, it is retained, otherwise it is discarded. For the emitted energy envelope characteristics, a numerical threshold judgment is performed, requiring the energy value to be ≥13 energy units; if it meets this requirement, it is retained, otherwise it is discarded. For the emitted direction perturbation amplitude, an amplitude judgment is performed, requiring the emitted direction perturbation amplitude to be ±2°; if it meets this requirement, it is retained, otherwise it is discarded. For the directional distribution pattern, a set matching judgment is performed, requiring the directional distribution pattern to include five directions: -2°, -1°, 0°, 1°, and 2°; if it includes these directions, it is retained, otherwise it is discarded. All retained acoustic fragment components are then aggregated to form a component candidate subset.

[0055] Subsequently, within the candidate component subset, the state attributes of acoustic segment components are introduced as secondary screening constraints. Based on the reliability evolution trend, information density distribution, and spatial consistency index of each acoustic segment component, an acoustic segment component set is established. Specifically, for each acoustic segment component, the echo efficiency over the most recent 10 acquisition cycles is calculated. Echo efficiency = effective echo frames / total echo frames. For example, if the total echo frames per cycle are 50, and the effective echo frames in the first cycle are 45, the efficiency is 0.90; if the effective echo frames in the tenth cycle are 48, the efficiency is 0.96. The reliability is taken as the average of the echo efficiency over the 10 cycles, and the reliability evolution trend is the efficiency of the tenth cycle minus the efficiency of the first cycle, i.e., 0.96 - 0.90 = 0.06. The information density distribution is based on the effective velocity profile formed per unit time. Point counting is performed. For example, if 40 depth unit velocity values ​​are output within 1 second, and 32 of them are valid units, then the information density is 32 points / s. The spatial consistency index is calculated based on the root mean square error of the velocity difference sequence between adjacent depth units. For example, if the velocity difference between adjacent 0.5m depth positions is 0.10, 0.12, 0.09, and 0.11m / s, the root mean square error is 0.000125m / s². Acoustic segment components with a confidence level ≥0.90, an information density ≥30 points / s, and a spatial consistency index root mean square error ≤0.0005m / s² are retained and summarized to establish an acoustic segment component set.

[0056] Finally, a joint constraint evaluation is performed on the emitted energy coverage, directional perturbation distribution, and echo time window overlap of the acoustic segment component set. In this process, the emitted energy coverage of the acoustic segment component set is checked, and the minimum energy value of each acoustic segment component in the set is taken, requiring the minimum value to be ≥13 energy units to ensure that there are no insufficient energy components in the combination. The directional perturbation distribution of the acoustic segment component set is checked, and the union of all directional distribution patterns in the set is taken, requiring the union to include -2°, -1°, 0°, 1°, and 2°. The echo time window overlap is calculated, where overlap = intersection time length / smaller time window length, for example, time windows of 0.0... The intersection of the time windows 106s~0.0160s and 0.0120s~0.0170s is 0.0120s~0.0160s, with an intersection length of 0.0040s. The shorter time window length is 0.0160−0.0106=0.0054s, and the overlap is 0.0040 / 0.0054≈0.7407. The required overlap is ≥0.60. The acoustic segment components that simultaneously satisfy the constraints of emission energy coverage, directional perturbation distribution, and echo time window overlap are combined and output as multidimensional matching and screening results.

[0057] Furthermore, in the method provided in the application embodiments, after configuring the acoustic segment component combination according to the multi-dimensional matching and filtering results and setting the execution order, the acoustic transmission and reception processing is performed, which further includes: Based on the differences in the transmission energy coverage, directional perturbation distribution, and echo time window width among the various acoustic segment component combinations in the multidimensional matching and screening results, the acoustic segment components are classified into coverage roles. The coverage roles include basic coverage components used to establish the acoustic interpretation boundary of the flow field expression region and enhanced coverage components used to refine the flow field structure inside the acoustic interpretation boundary. For the same flow field expression region, at least one acoustic segment component is selected from the basic coverage component and the enhanced coverage component respectively to construct an acoustic segment component combination that satisfies the spatial coverage integrity constraint and information complementarity constraint of the flow field expression region. Based on the coverage role of each acoustic segment component in the acoustic segment component combination and the consistency evaluation results in the multidimensional matching and screening results, the execution order of the acoustic segment components is determined, and acoustic transmission and reception processing are performed.

[0058] In this embodiment, based on the differences in emission energy coverage, directional perturbation distribution, and echo time window width among the acoustic segment components in the multidimensional matching and screening results, when classifying the coverage roles of acoustic segment components, the emission energy envelope characteristics, directional distribution pattern, and echo time window width of each acoustic segment component are first read. These physical attributes are then compared item by item with the target depth range, directional coverage requirements, and echo reception time interval of the flow field expression region. When the emission energy envelope characteristic of a certain acoustic segment component is not less than 13 energy units, its directional distribution pattern covers −2°, −1°, 0°, 1°, and 2°, and its echo time window width covers the echo reception interval corresponding to 0.0106s to 0.0160s, this acoustic segment component is determined as a basic coverage component, used to establish the acoustic interpretation boundary of the flow field expression region. When the emission energy envelope characteristics of a certain acoustic segment component meet the target depth requirements, but its directional distribution pattern only covers a portion of the aforementioned directional set, or its echo time window width only covers a portion of the time interval from 0.0106s to 0.0160s, the acoustic segment component is identified as an enhanced coverage component. This component is used to refine the flow field structure within the acoustic interpretation boundary. The enhanced coverage component improves the echo information density in the local area by using a subset of the directional distribution pattern or a narrower echo time window width, thereby concentrating acoustic sampling in a specific direction or a specific depth interval.

[0059] After completing the coverage role division, for the same flow field expression region, at least one acoustic segment component is selected from the basic coverage component and the enhanced coverage component to construct an acoustic segment component combination. During the construction process, the spatial coverage integrity constraint is first checked. The selected basic coverage component must simultaneously cover the entire range of the flow field expression region in both the time and depth dimensions in terms of emitted energy coverage range, directional disturbance distribution, and echo time window width, thus ensuring that the acoustic interpretation boundary of the flow field expression region can be completely established. Under the premise that the spatial coverage integrity constraint is satisfied, the information complementarity constraint is then checked. The selected enhanced coverage component must form a non-repeating coverage relationship with the basic coverage component in terms of directional distribution pattern or echo time window width. The non-repeating coverage relationship is obtained by comparing the set of directional distribution patterns or echo time window intervals. If the direction or time interval covered by the enhanced coverage component completely overlaps with the basic coverage component, the information complementarity constraint is not satisfied. If there is a direction or time interval not covered by the basic coverage component alone, the information complementarity constraint is satisfied. Thus, the acoustic segment component combination that satisfies both the spatial coverage integrity constraint and the information complementarity constraint of the flow field expression region is determined.

[0060] After determining the acoustic segment component combination, the execution order of the acoustic segment components is determined based on the coverage role of each acoustic segment component in the acoustic segment component combination and its consistency evaluation result in the multi-dimensional matching and screening results. The consistency evaluation result is obtained by jointly judging the emission energy coverage, directional perturbation distribution and echo time window overlap. The emission energy coverage is confirmed by judging whether the emission energy envelope feature is not less than 13 energy units, the directional perturbation distribution is confirmed by judging whether the directional distribution pattern contains the corresponding directional element, and the echo time window overlap is confirmed by comparing whether the ratio of the intersection length of the echo time windows of different acoustic segment components to the length of the smaller time window is not less than 0.60. During the execution order determination process, the basic coverage component is executed before the enhanced coverage component. Within the same coverage role, acoustic segment components with echo time window widths ranging from 0.0106s to 0.0160s and echo time window overlap of not less than 0.60 are executed first. Then, acoustic segment components with echo time window widths of their sub-intervals are executed. Finally, acoustic transmission and reception processing are executed sequentially according to the determined execution order, so that the basic coverage component forms the acoustic interpretation boundary of the flow field expression region, and the enhanced coverage component is used to refine the flow field structure within the acoustic interpretation boundary.

[0061] Step S4: For each executed acoustic segment component, update its state attributes based on the corresponding echo response characteristics. The state attributes include component confidence, information density, or spatial consistency index. In this embodiment, for each executed acoustic segment component, after completing acoustic transmission and reception, the state attributes of the component are updated based on the corresponding echo response characteristics. These echo response characteristics include the echo energy attenuation curve, effective scattering layer distribution characteristics, and echo phase stability characteristics. By mapping the echo energy attenuation curve to the component reliability update space, mapping the effective scattering layer distribution characteristics to the information density update space, and mapping the echo phase stability characteristics and echo time consistency characteristics to the spatial consistency index update space, the state attributes of the acoustic segment component—component reliability, information density, and spatial consistency index—are updated.

[0062] Furthermore, in the method provided in the application embodiments, updating the state attributes of each executed acoustic segment component based on the corresponding echo response characteristics further includes: After the acoustic segment component completes its corresponding acoustic transmission and reception, the echo response feature set bound to the acoustic segment component is extracted. The echo response feature set includes the echo energy attenuation curve, echo phase stability features, and effective scattering layer distribution features. The echo response feature set is then mapped to the update space of the acoustic segment component's state attributes. Specifically, the echo energy attenuation curve is used to update the component credibility of the acoustic segment component; the effective scattering layer distribution features are used to update the information density of the acoustic segment component; and the echo phase stability features and echo time consistency features are used to update the spatial consistency index of the acoustic segment component.

[0063] In this embodiment, after the acoustic segment component completes its corresponding acoustic transmission and reception, the original echo signal bound to the acoustic segment component is first analyzed to form an echo response feature set. Specifically, the echo amplitude sequence, echo phase sequence, and corresponding time sampling points and depth sampling points are obtained from the receiving channel. The echo energy attenuation curve is obtained by arranging the echo amplitude sequence in chronological order, and using the first valid echo amplitude as a reference value, the subsequent echo amplitudes are normalized to form a curve of echo amplitude changing with propagation time, which represents the energy change relationship of the acoustic signal along the propagation path. The echo phase stability feature is obtained by recording the echo phase values ​​of the same depth sampling point within a continuous sampling period and calculating the echo phase difference sequence between adjacent sampling periods. The effective scattering layer distribution feature is obtained by thresholding the echo amplitude of each depth sampling point. When the echo amplitude is not less than a preset effective echo threshold, the depth sampling point is marked as an effective scattering point. The continuous distribution of all effective scattering points in the depth dimension is statistically analyzed to form the effective scattering layer distribution feature.

[0064] After obtaining the echo response feature set, the component confidence level of the acoustic segment is updated. In this process, quantitative calculations are performed based on the echo energy attenuation curve. First, the echo energy attenuation curve formed by the current acoustic segment during this execution is selected and compared with the reference energy attenuation curve formed by the same acoustic segment during historical executions. The difference sequence of the corresponding amplitudes of the two energy attenuation curves is calculated at the same propagation time position. Then, the absolute value of the difference sequence is taken and its average value is calculated. When the average value is not greater than 10% of the average amplitude of the reference energy attenuation curve, the component confidence level of the acoustic segment is updated to remain unchanged or increase by a preset step size. When the average value is greater than 10% of the average amplitude of the reference energy attenuation curve, the component confidence level of the acoustic segment is decreased by a preset step size. Thus, the component confidence level numerically reflects the degree of deviation between the echo energy response of the acoustic segment under current water conditions and its historical steady state.

[0065] When updating the information density of an acoustic segment component, calculations are performed based on the distribution characteristics of the effective scattering layer. During this process, within the current execution cycle of the acoustic segment component, the number of depth sampling points marked as effective scattering points is counted, and the number of effective scattering points per unit time is calculated in conjunction with the corresponding time sampling length. For example, if 30 effective scattering points are counted within a 1-second time period, the information density is set to 30 points / second. Simultaneously, the length of continuous intervals of effective scattering points in the depth dimension is statistically analyzed. When the depth range covered by the continuous effective scattering interval is not less than 70% of the target depth range, the information density value is maintained or increased. When the continuous coverage depth range is less than 70% of the target depth range, the information density value is reduced by a preset ratio, ensuring that the information density numerically reflects the quantity and distribution of effective flow field information acquired by the acoustic segment component within the corresponding time and depth intervals.

[0066] When updating the spatial consistency index of an acoustic segment component, a joint calculation is performed based on echo phase stability characteristics and echo time consistency characteristics. The echo phase stability characteristic calculates the average and variance of the phase difference by statistically analyzing the echo phase difference sequence at the same depth sampling point within adjacent sampling periods. The echo time consistency characteristic calculates the average and variance of the arrival time difference by statistically analyzing the echo arrival time difference within adjacent sampling periods. When the variance of the phase difference is not greater than a preset phase consistency threshold and the variance of the echo arrival time difference is not greater than a preset time consistency threshold, the spatial consistency index of the acoustic segment component is updated to either maintain its original value or increase by a preset step size. When either variance exceeds the corresponding threshold, the spatial consistency index is decreased by a preset step size. This allows the spatial consistency index to quantitatively reflect the consistency of the echo response of the acoustic segment component at adjacent time and depth positions, completing the update of the acoustic segment component's state attributes based on echo response characteristics.

[0067] Furthermore, the method provided in the application embodiments also includes: During the state attribute update process, the coordinate index corresponding to the acoustic segment component is introduced to perform coordinate association weighted update, so that the same acoustic segment component forms a differentiated state attribute evolution trajectory under different time coordinates or depth coordinates.

[0068] In this embodiment of the application, during the state attribute update process, when the coordinate index corresponding to the acoustic segment component is introduced to perform coordinate association weighted update, a coordinate index binding table is first established for each acoustic segment component within the acoustic flow field reference coordinate system framework, so that each acoustic segment component is simultaneously bound to a time coordinate index and a depth coordinate index. In the storage structure, state attribute record entries are established for the same acoustic segment component according to different coordinate indices. The state attribute record entries contain three fields: component credibility, information density, and spatial consistency index, thereby ensuring that the state attributes of the same acoustic segment component under different time coordinate indices or depth coordinate indices can be read and written independently.

[0069] After the acoustic segment component completes acoustic transmission and reception and obtains the echo response characteristics, a coordinate association retrieval method is used to determine the coordinate index corresponding to this update. Specifically, the time coordinate index and depth coordinate index of the acoustic segment component are read, and the record entries that are completely consistent with the time coordinate index and depth coordinate index are located in the status attribute record entries. At the same time, the record entries of the same acoustic segment component under adjacent time coordinate indexes and adjacent depth coordinate indices are retrieved. For example, the record entries at one index position before and after the current time coordinate index and one index position above and below the current depth coordinate index are retrieved to participate in the coordinate association weighted update.

[0070] After determining the record entries to be updated, a fixed-weight allocation method is used to generate coordinate association weights. In this process, a weight of 0.50 is assigned to record entries with a time coordinate index difference of 0, a weight of 0.25 is assigned to record entries with a time coordinate index difference of 1, a weight of 0.50 is assigned to record entries with a depth coordinate index difference of 1, and a weight of 0.25 is assigned to record entries with a depth coordinate index difference of 0. The time weight and the depth weight are then multiplied to obtain the coordinate association weight for each record entry. For example, the coordinate association weight for a record entry with a time difference of 0 and a depth difference of 1 is 0.50 × 0.25 = 0.125, the coordinate association weight for a record entry with a time difference of 1 and a depth difference of 0 is 0.25 × 0.50 = 0.125, and the coordinate association weight for a record entry with a time difference of 0 and a depth difference of 0 is 0.50 × 0.50 = 0.25. All coordinate association weights are then normalized so that their sum equals 1.

[0071] After obtaining the coordinate association weights, a weighted fusion method is used to perform coordinate association weighted updates. This involves writing the component reliability, information density, and spatial consistency index calculated from the current echo response characteristics as the current values ​​into the calculation items participating in the fusion. The component reliability, information density, and spatial consistency index of each retrieved historical record entry are then weighted and summed according to their coordinate association weights to obtain the updated component reliability, information density, and spatial consistency index. The updated component reliability is equal to the sum of the products of the component reliability of each participating record entry and its coordinate association weight. The information density and spatial consistency index are obtained using the same weighted summation method. Finally, the updated state attributes are written back to the state attribute record entry that is completely consistent with the current time coordinate index and depth coordinate index.

[0072] Through the above-mentioned processes of coordinate index binding, coordinate association retrieval, fixed weight allocation, and weighted fusion write-back, the same acoustic segment component can form independent component credibility, information density, and spatial consistency index update results under different time coordinate indices or depth coordinate indices, thereby forming differentiated state attribute evolution trajectories.

[0073] Furthermore, the method provided in the application embodiments also includes: During the state attribute update process of acoustic segment components, if the component reliability or spatial consistency index of an acoustic segment component is lower than the preset stability threshold within two consecutive acquisition cycles, the corresponding acoustic segment component will be marked as a low-stability component, and weight attenuation or frequency restriction will be applied.

[0074] In this embodiment, during the state attribute update process of the acoustic segment component, to continuously monitor the stability of the acoustic segment component, the historical values ​​of its component reliability and spatial consistency index are first saved in the state attribute record structure according to the time coordinate index order. The state attributes corresponding to two adjacent acoustic acquisitions are then associated as a continuous acquisition cycle pair. After each state attribute update, the component reliability value and spatial consistency index value of the acoustic segment component in the current acquisition cycle and the previous acquisition cycle are read and compared with preset stability thresholds. The preset stability threshold for component reliability is set to 0.90, and the preset stability threshold for spatial consistency index is set to 0.80. When the component reliability is less than 0.90 in two consecutive acquisition cycles, or the spatial consistency index is less than 0.80 in two consecutive acquisition cycles, it is determined that the acoustic segment component does not meet the stability requirements under the current time depth conditions.

[0075] After completing the stability determination of the continuous acquisition cycle, a low-stability component marking operation is performed on the acoustic segment components that meet the above determination conditions. In this process, a low-stability component marking field is written into the state attribute record of the acoustic segment component, and the marking is bound and stored with the corresponding time coordinate index and depth coordinate index, so that the acoustic segment component is identified as a low-stability component at that time and depth position, without affecting its state attribute record under other time coordinate indexes or depth coordinate indices.

[0076] After an acoustic segment component is marked as a low-stability component, a weight attenuation process is applied to it. A fixed-proportion attenuation method is used to adjust the weight value of the acoustic segment component in the subsequent coordinate association weighted update and multi-dimensional matching screening. The coordinate association weight corresponding to the acoustic segment component is multiplied by an attenuation coefficient of 0.50, so that its influence on the update results of component credibility, information density and spatial consistency index in the weighted fusion calculation is halved. At the same time, the weights of other unmarked acoustic segment components remain unchanged, thereby reducing the influence of low-stability components on the overall state assessment results.

[0077] When limiting the execution frequency of unstable components, a counting method based on acquisition cycles is used to control their calling frequency. In this process, an execution counter is set in the acoustic segment component scheduling record, and it is stipulated that the execution count of an unstable component will not exceed once within five consecutive acoustic acquisition cycles. When the execution count reaches the upper limit, the acoustic segment component will be temporarily excluded from acoustic transmission and reception during subsequent acoustic acquisition scheduling processes until its component reliability or spatial consistency index reaches or exceeds the corresponding preset stability threshold again within two consecutive acquisition cycles. After this, the unstable component is removed from the list and its normal weight and execution frequency are restored.

[0078] Furthermore, the method provided in the application embodiments also includes: The mobile ADCP200 is equipped with a storage module 150. During the data acquisition process, the acquired data is synchronously backed up to the storage module 150 for storage management.

[0079] In this embodiment, the mobile ADCP200 is equipped with a storage module 150. During data acquisition, after acoustic transmission and echo reception are completed and corresponding acquisition data is formed, the acquisition data is copied and synchronously written to the storage module 150 while being written to the main storage location. This ensures that the storage module 150 stores a copy of the data corresponding to the current acquisition process in real time. The storage module 150 manages the synchronously backed-up acquisition data according to the acquisition time sequence and retains the time and depth information associated with the acquisition data. This provides reliable data support for data reading, transmission, or data recovery in case of abnormal situations during continuous data acquisition.

[0080] Step S5: Generate acquisition results by performing correlation analysis between the acoustic segment components with updated state attributes and the coordinate index of the acoustic flow field reference coordinate system frame.

[0081] In this embodiment, when performing coordinate index association analysis between acoustic segment components with updated state attributes and the acoustic flow field reference coordinate system frame, the acoustic segment components with updated state attributes are associated with coordinate indices based on the time and depth coordinates of the acoustic flow field reference coordinate system frame. Acoustic segment components with the same time and depth coordinates are grouped into corresponding coordinate-associated component sets. Subsequently, for each coordinate-associated component set, a comprehensive weight parameter is formed to characterize the reliability of the flow field representation in that coordinate region based on the component credibility, information density, and spatial consistency index of each acoustic segment component within the set. Finally, the echo observation results formed by multiple acoustic segment components in that coordinate region are weighted and fused using the comprehensive weight parameter to generate acquisition results that correspond one-to-one with the acoustic flow field reference coordinate system frame in terms of time and depth coordinates.

[0082] Furthermore, in the method provided in the application embodiments, the generation of acquisition results based on the correlation analysis between the acoustic segment component with updated state attributes and the coordinate index of the acoustic flow field reference coordinate system frame also includes: Based on the time and depth coordinates of the acoustic flow field reference coordinate system, the acoustic segment components involved in the acquisition are aggregated to form multiple coordinate-related component sets. For each coordinate-related component set, a comprehensive weight parameter is generated to characterize the reliability of the flow field expression in the corresponding coordinate region, based on the component reliability, information density, and spatial consistency index of each acoustic segment component. Based on the comprehensive weight parameter, the echo observation results formed by multiple acoustic segment components in the corresponding coordinate region are weighted and fused to generate acquisition results that correspond one-to-one with the acoustic flow field reference coordinate system.

[0083] In this embodiment, when the acoustic segment components participating in the acquisition are aggregated according to the time coordinates and depth coordinates of the acoustic flow field reference coordinate system frame, the time coordinate index and depth coordinate index bound to each acoustic segment component are read one by one. The time coordinate index and the depth coordinate index are consistent as the aggregation condition. The acoustic segment components that meet the condition and their echo observation results are written into the same aggregation set. At the same time, the time coordinate index and depth coordinate index identifiers corresponding to the set are retained in the aggregation set to limit the coordinate area range corresponding to the set, thus forming multiple coordinate-associated component sets.

[0084] Subsequently, for each coordinate-associated component set, a comprehensive weight parameter is generated based on the component reliability, information density, and spatial consistency index of each acoustic segment component. In this process, firstly, the three state attributes of component reliability, information density, and spatial consistency index of each acoustic segment component within the coordinate-associated component set are read, and linear normalization is performed within the coordinate-associated component set respectively, ensuring that the normalized value of each state attribute falls within the range of 0 to 1. The normalized value = current value − minimum value / maximum value − minimum value. After obtaining the three normalized values, a weighted sum is calculated according to a preset ratio to obtain the comprehensive weight parameter: Comprehensive weight parameter = 0.5 × component reliability normalized value + 0.3 × information density normalized value + 0.2 × spatial consistency index normalized value. This comprehensive weight parameter is then correlated with the corresponding acoustic segment component record in the coordinate-associated component set, generating a comprehensive weight parameter used to characterize the reliability of the flow field expression in the corresponding coordinate region.

[0085] Finally, based on the comprehensive weighting parameter, when performing weighted fusion processing on the echo observation results formed by multiple acoustic segment components within the corresponding coordinate region, the echo observation result of each acoustic segment component in the coordinate-related component set and its corresponding comprehensive weighting parameter are first read. A weighted average calculation is then performed on the echo observation results, and the fusion result is calculated as Σ echo observation result × comprehensive weighting parameter / Σ comprehensive weighting parameter. The fusion result is then written to the time coordinate index and depth coordinate index corresponding to the coordinate-related component set. This weighted fusion and writing process is repeated for all coordinate-related component sets within the acoustic flow field reference coordinate system frame, generating acquisition results that correspond one-to-one with the acoustic flow field reference coordinate system frame.

[0086] By constructing the aforementioned acoustic flow field reference coordinate system framework, establishing the acoustic segment component pool, and dynamically filtering and updating the state of the acoustic segment components, a complete and closed-loop acoustic data acquisition and processing process can be formed on a single mobile ADCP200 unit. This process uses time coordinate indices and depth coordinate indices as unified constraints, ensuring that acoustic emission, echo reception, state attribute updates, and acquisition result generation all revolve around the same spatiotemporal reference. This guarantees that the flow field data obtained by a single mobile ADCP200 unit at different time and depth locations have consistent expression rules and comparability.

[0087] During this process, the mobile ADCP200 sends the hydrological data generated during the acquisition process to the connected data acquisition terminal 100 via a communication connection. The data acquisition terminal 100 then buffers, encapsulates, and forwards the acquired data.

[0088] When multiple mobile ADCP200s participate in measurements simultaneously, each mobile ADCP200 performs the aforementioned acoustic data acquisition and processing procedures, and establishes a data and command interaction relationship with the cloud server 300 via wireless communication through its corresponding data acquisition terminal 100. The cloud server 300 sends acquisition timing sequences and parameters to the multiple mobile ADCP200s based on a unified time reference. These timing sequences and parameters are transmitted to each data acquisition terminal 100 via wireless communication links and then to the corresponding mobile ADCP200s, enabling each mobile ADCP200 to conduct acoustic acquisition operations at different river cross-sections or measurement points according to consistent time and depth coordinate indexing rules. Therefore, the acquisition results from different measurement points can be aggregated and differentiated based on time and spatial coordinates, achieving synchronous or asynchronous acquisition of hydrological data from multiple rivers.

[0089] During acoustic data acquisition and processing, the mobile ADCP200 can switch between different operating modes according to the measurement task requirements. When the mobile ADCP200 is configured as a current meter, it continuously performs acoustic acquisition at a designated location and repeatedly samples the same vertical position under the time and depth conditions defined by the acoustic flow field reference coordinate system frame, thereby improving the stability of flow velocity measurement under low flow velocity conditions by extending the single-point acquisition time. When the mobile ADCP200 is configured as a timed operation mode, it periodically triggers the acoustic transmission and echo reception process according to the preset start time, end time and acquisition interval, and completes data acquisition and result generation according to the established acoustic segment component screening and status update rules.

[0090] In the event of limited or interrupted communication conditions, the data generated during the acquisition process can be locally cached by the data acquisition terminal 100 and retransmitted via wireless or satellite communication after the communication conditions are restored, so that the acquired data can completely correspond to its time coordinate index and depth coordinate index.

[0091] In addition, the data acquisition terminal 100 can also establish a data interaction relationship with the shore receiver 400 through short-range communication for on-site parameter configuration, status query or data reading operations. The shore receiver 400 can establish a connection with the client 500 to realize the display, management or archiving of the acquired data.

[0092] By means of the above method, the data acquisition method of a single mobile ADCP200 is extended to the collaborative operation scenario of multiple mobile ADCP200s. Combined with the wireless communication, satellite communication and short-range communication of the data acquisition terminal 100 and the onshore receiver 400, the acquired data can be transmitted and collected under different communication conditions. Thus, multiple measurement points can complete data acquisition and processing according to a unified acoustic flow field reference coordinate system framework, forming an overall acquisition scheme suitable for the measurement needs of multiple river hydrological cross sections.

[0093] In summary, the embodiments of this application have at least the following technical effects: Before performing acoustic acquisition with the mobile ADCP200, this application constructs a set of acoustic flow field reference coordinate system frameworks to define the water flow field in the time and depth dimensions, based on preset flow field expression targets. Based on this framework, acoustic emission energy, emission direction disturbances, and echo events are combined into multiple acoustic segment components, and a corresponding reference coordinate index is assigned to each component, establishing an acoustic segment component pool. During acoustic acquisition, based on the flow field expression requirements of different coordinate regions within the acoustic flow field reference coordinate system framework, multiple acoustic segment components are selected from the pool and arranged in a preset order to perform acoustic transmission and reception. For each executed acoustic segment component, the state attributes of the component are updated based on the corresponding echo response characteristics. These state attributes include component reliability, information density, or spatial consistency indicators. Acquisition results are generated based on the correlation analysis between the acoustic segment components with updated state attributes and the coordinate indexes of the acoustic flow field reference coordinate system framework. This invention addresses the technical problem in the prior art where the mobile ADCP200 data acquisition process struggles to account for flow field changes under different time and depth conditions, leading to insufficient reliability of the acquisition results. By applying unified constraints to the acquisition process based on an acoustic flow field reference coordinate system and dynamically combining acoustic acquisition components, the invention achieves the technical effect of improving the stability and reliability of the mobile ADCP200 data acquisition results under different spatiotemporal conditions.

[0094] Example 4: Simplified workflow.

[0095] like Figure 5 As shown, an integrated ADCP data acquisition system includes: The coordinate system framework construction module 610 is used to construct a set of acoustic flow field reference coordinate system frameworks to define the water flow field in the time and depth dimensions, based on the preset flow field expression target, before the ADCP performs acoustic acquisition. The component pool establishment module 620 is used to combine acoustic emission energy, emission direction disturbances, and echo events into multiple acoustic segment components based on the acoustic flow field reference coordinate system framework, and assign a corresponding reference system coordinate index to each acoustic segment component to establish an acoustic segment component pool. The transmission and reception module 630 is used to, during the acoustic acquisition process, based on... To meet the flow field representation requirements of different coordinate regions within the acoustic flow field reference coordinate system framework, multiple acoustic segment components are selected from the acoustic segment component pool and arranged in a preset order to perform acoustic transmission and reception. The update module 640 is used to update the state attributes of each executed acoustic segment component based on the corresponding echo response characteristics. The state attributes include component reliability, information density, or spatial consistency index. The analysis module 650 is used to perform correlation analysis between the acoustic segment components with updated state attributes and the coordinate index of the acoustic flow field reference coordinate system framework to generate acquisition results.

[0096] Example 5

[0097] like Figure 2-4 As shown, in order to meet the observation requirements of flow velocity at a specific depth in traditional hydrological surveys, this invention, after generating high-precision multidimensional acquisition results through step S5, also includes a data dimensionality reduction processing step for the flow velocity meter measurement mode.

[0098] The waterproof housing 110 has a power button 111, a status indicator light 112, and a power display screen 113 on its panel. On the other side, there is a charging port 115, a radio antenna port 116, and a heading antenna port 117. The data acquisition terminal 100 has a connector 170 to be fixed on an external bracket or float as a hydrological telemetry terminal. The main control module 120 supports a timed sleep and wake-up mechanism. When the preset sampling period is reached, the power module 160 is woken up to power the mobile ADCP200 to perform fixed-point measurement.

[0099] After completing step S5 to generate the acquisition results, the method also includes a data dimensionality reduction processing step for the flow meter measurement mode. The main control module 120 can perform average segmented measurement on multiple points in the vertical direction according to the number of measurement points set by the user, extract and interpolate to calculate the single-point flow velocity value at the depth position of multiple points below the water surface, and use the corresponding formula to obtain and output the single-point vertical average flow velocity. For example, according to river hydrological standards, when the water depth H is less than 1.5m, a single-point method can be used to measure data at 0.6H or 0.5H. Similarly, when the water depth H is greater than or equal to 1.5m and less than 3.0m, a two-point method can be used, that is, to obtain values ​​at 0.2H and 0.8H. When the water depth H>3m and H<5m, three-point measurement is also set up in the same way. Similarly, when the water depth H>5m, a six-point method can be used, or the number of sampling points can be set by the user when the water depth is even greater. After determining the number of sampling points, the main control module 120 extracts the flow velocity value at the corresponding depth and uses the corresponding single-point measurement data to obtain the average flow velocity under the vertical.

[0100] Therefore, the mobile ADCP200 was used as a flow meter for fixed-point measurement.

[0101] The method also includes a timed autonomous measurement and control step: the main control module 120 obtains the measurement time, time interval, and preheating power supply parameters sent by the cloud server 300 or the client; when the set time is reached, the autonomous control power module 160 preheats the mobile ADCP200 and executes the flow meter measurement mode; after completion, the power supply to the peripheral device is automatically disconnected and the collected files are forwarded to the designated cloud server 300, realizing remote cluster control of multiple cloud flow measurement terminals.

[0102] Specifically, the data acquisition terminal 100 can be fixedly installed on a bracket or floating drum in the center of the river channel as a hydrological remote sensing terminal unit (RTU) via the clamp structure outside the waterproof housing 110. The mobile ADCP 200 is placed upside down below the water surface. In current meter mode, the main control module 120 performs average segmented measurements on multiple points in the vertical direction according to the number of measurement points set by the user. It extracts and interpolates to calculate the single-point flow velocity values ​​at the depth positions of multiple points below the water surface, and uses the corresponding formula to obtain and output the single-point vertical average flow velocity; thus successfully using the mobile ADCP as a fixed-point current meter.

[0103] The main control module 120 supports a timed sleep and wake-up mechanism. It can obtain the measurement time and interval from the cloud server 300. Before the set time is reached, it autonomously controls the power module 160 to preheat the mobile ADCP200 and execute the flow meter measurement mode. After the measurement is completed, it automatically disconnects the power supply to the peripheral devices, forwards the collected data to the cloud server 300, and then enters a low-power sleep state. This device enables remote cluster control of multiple integrated terminals.

[0104] In the above embodiments, the descriptions of each embodiment have different focuses. For parts not described in detail in a certain embodiment, please refer to the relevant descriptions in other embodiments.

[0105] Obviously, the above embodiments of the present invention are merely examples for clearly illustrating the present invention, and are not intended to limit the implementation of the present invention. Those skilled in the art can make other variations or modifications based on the above description. It is neither necessary nor possible to exhaustively describe all embodiments here. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of the present invention should be included within the scope of protection of the claims of the present invention.

Claims

1. An integrated ADCP data acquisition system, characterized in that, include: The system includes a data acquisition terminal (100), a mobile ADCP (200), a cloud server (300), a shore-based receiver (400), and a client (500). The data acquisition terminal (100) includes a waterproof housing (110), and a main control module (120), a multi-mode communication module (130), a positioning and orientation module (140), a storage module (150), and a power module (160) disposed inside the waterproof housing (110). The main control module (120) is electrically connected to the multi-mode communication module (130), the positioning and orientation module (140), the storage module (150), and the power module (160), respectively; The waterproof housing (110) is provided with an ADCP cable port (114), and the main control module (120) is electrically connected to the external mobile ADCP (200) through the ADCP cable port (114). The main control module (120) is used to control the power module (160) to provide power to the mobile ADCP (200) and receive the underlying echo data. It synchronously acquires the position and heading information of the positioning and orientation module (140), processes it, and then sends it to the cloud server (300) or the shore receiver (400) through the multi-mode communication module (130). The client (500) is connected to the cloud server (300), the shore receiver (400), and the data acquisition terminal (100) for data interaction.

2. The integrated ADCP data acquisition system according to claim 1, characterized in that, The multimode communication module (130) includes a network unit (131) and a radio unit (132). The main control module (120) communicates bidirectionally with the cloud server (300) via the network unit (131) using the MQTT protocol through the 5G / 4G network; the main control module (120) establishes a long-distance radio station transparent transmission connection with the shore receiver (400) through the radio station unit (132). The client (500) includes a PC client and a mobile application (APP). The client (500) includes a multi-link communication architecture: it connects to the shore receiver (400) via USB or Bluetooth interface to obtain radio transmission data, communicates directly with the data acquisition terminal (100) via 5G / 4G network, and establishes communication with the cloud server (300) via the Internet.

3. The integrated ADCP data acquisition system according to claim 2, characterized in that, During the data acquisition process, the main control module (120) prioritizes sending data to the cloud server (300) through the network unit (131), and then forwards it to the client (500) through the cloud server (300). During the data collection process, the data is synchronously stored in the storage module (150). When the network signal is lost, the data can be transmitted to the shore receiver (400) by connecting to the radio station unit (132), and transmitted to the client (500) via wired or Bluetooth through the shore receiver (400). When network recovery is detected, historical network outage data in the storage module (150) is compensated and resumed while real-time data is being sent.

4. The integrated ADCP data acquisition system according to claim 1, characterized in that, The positioning and orientation module (140) is used to receive satellite signals for RTK positioning and to obtain heading information; The main control module (120) synchronously acquires the RTK positioning information and heading information output by the positioning and orientation module (140), combines the bottom echo data of the mobile ADCP (200), performs spatial coordinate alignment and error elimination, and extracts flow velocity data and outputs RTK positioning data based on the aligned coordinates, so as to simultaneously realize the measurement of water flow velocity and direction and underwater topography.

5. The integrated ADCP data acquisition system according to claim 1, characterized in that, The waterproof housing (110) has a power button (111), a status indicator (112) and a power display (113) on its panel, and a charging port (115), a radio antenna port (116) and a heading antenna port (117) on the other side. The data acquisition terminal (100) is provided with a connector (170) on the outside. The data acquisition terminal (100) is fixed to an external bracket or floating drum as a hydrological telemetry terminal through the connector (170). The storage module (150) is equipped with a local memory card, and the power module (160) is equipped with a battery pack for providing operating power.

6. The integrated ADCP data acquisition system according to claim 1, characterized in that, The main control module (120) supports a timed sleep and wake-up mechanism. After obtaining the measurement time and preheating power supply parameters, it wakes up the power supply module (160) when the set time is reached to preheat the mobile ADCP (200) and execute the fixed-point flow meter flow measurement mode. When the fixed-point flow meter is executed, the main control module (120) performs average segmented measurement on multiple points in the vertical direction according to the number of measurement points set by the user, extracts and interpolates to calculate the single-point flow velocity value at the depth position of multiple points below the water surface, and uses the corresponding formula to obtain and output the single-point vertical average flow velocity. After the measurement is completed, the power supply to the external device is automatically disconnected and the data is forwarded, enabling remote cluster control of multiple cloud flow measurement terminals.

7. The integrated ADCP data acquisition system according to claim 1, characterized in that, The main control module (120) has a built-in acoustic acquisition program based on component pool adaptive matching; When receiving the bottom echo data collected by the mobile ADCP (200), the main control module (120) dynamically generates and combines multiple acoustic segment components according to the expression requirements of the water flow field in the time and depth dimensions to adjust the energy and direction disturbance of the acoustic emission in real time, and performs weighted fusion based on the echo response characteristics to update the weight state of each component.

8. An integrated ADCP data acquisition method, characterized in that, The method, applied to the integrated ADCP data acquisition system as described in any one of claims 1-7, comprises: Step S1: Before ADCP performs acoustic acquisition, based on the preset flow field expression target, construct a set of acoustic flow field reference coordinate system frameworks to limit the water flow field in the time and depth dimensions; Step S2: Based on the acoustic flow field reference coordinate system framework, combine acoustic emission energy, emission direction disturbance and echo events into multiple acoustic segment components, and assign corresponding reference coordinate indices to establish an acoustic segment component pool; Step S3: During the acoustic acquisition process, based on the flow field expression requirements of different coordinate regions within the acoustic flow field reference coordinate system frame, multiple acoustic segment components are selected from the acoustic segment component pool and arranged in a preset order to perform acoustic transmission and reception. Step S4: For each executed acoustic segment component, update its state attributes based on the corresponding echo response characteristics. The state attributes include component confidence, information density, or spatial consistency index. Step S5: Generate acquisition results by performing correlation analysis between the acoustic segment components with updated state attributes and the coordinate index of the acoustic flow field reference coordinate system frame.

9. The method according to claim 8, characterized in that, The step S3, which involves selecting acoustic segment components from the acoustic segment component pool to perform acoustic transmission and reception, specifically includes: By introducing expression consistency constraints, the time and depth dimensions are jointly divided to form multiple flow field expression regions determined by the gradient distribution of flow field changes and the stability distribution of historical echoes. A set of regional expression requirement parameters is generated based on expression consistency constraints, and the parameter set is mapped to the physical property space of the acoustic segment components respectively; wherein the requirement parameter for sensitivity to flow field changes is mapped to the emission energy envelope characteristics and echo time window width, and the requirement parameter for vertical resolution consistency is mapped to the emission direction disturbance amplitude and direction distribution pattern; Based on the mapping relationship, a primary constraint screening is performed to establish a candidate subset of components. State attributes are introduced as secondary constraints, and joint constraint evaluation of emission energy coverage, directional perturbation distribution, and echo time window overlap is performed to establish multidimensional matching screening results.

10. The method according to claim 8, characterized in that, Step S4 specifically includes: extracting the echo response feature set bound to the acoustic segment component, and using the echo energy attenuation curve to update the component credibility, the effective scattering layer distribution feature to update the information density, and the echo phase stability and temporal consistency feature to update the spatial consistency index; in this process, coordinate index is introduced to perform coordinate association weighted update, and when the component credibility or spatial consistency index is lower than the preset stability threshold for two consecutive periods, it is marked as a low-stability component and weight attenuation or frequency restriction is applied.

Images