Intelligent Sampling Method and System for Aquatic Sediments Based on Cyclone Sorting by Unmanned Aerial Vehicles

Abstract

The present application relates to the technical field of intelligent sampling, in particular to a UAV water system sediment intelligent sampling method and system based on cyclone sorting, comprising the following steps: collecting disturbance trajectory and cyclone data, identifying stable entrance, screening alignment interval, executing screen alignment, and generating sampling record. In the present application, the stable section is calibrated by superimposing wind speed direction fluctuation and rectifier plate trajectory change, the screening range is locked to the alignable interval by combining the multi-parameter mapping of rotation speed and particle density, the sediment movement state is captured by the screen in the sediment layer, and the whole process sampling sequence is constructed by the coordination of rectification action and screen operation timing, which can dynamically extract the real water body disturbance characteristics, match the sediment movement law, improve the sampling trigger response accuracy, strengthen the screening alignment accuracy under the coupling of multiple factors, and realize the accurate capture of the target section under the interweaving interference of air flow disturbance and particle sedimentation process, and stably maintain the particle layered structure.

Description

Technical Field

[0001] This invention relates to the field of intelligent sampling technology, and in particular to an intelligent sampling method and system for aquatic sediments by unmanned aerial vehicles based on vortex sorting. Background Technology

[0002] The field of intelligent sampling technology involves a technical system for sampling, collecting, and transmitting target media using automated and intelligent equipment. It mainly includes sample collection devices, execution control systems, sampling path planning methods, and sample identification and processing technologies. It is widely used in environmental monitoring, hydrological surveys, agricultural testing, and resource exploration. Among them, the UAV aquatic sediment sampling method refers to the technical method of collecting surface or bottom sediments in water bodies such as rivers, lakes, and wetlands using remotely controlled or pre-programmed aircraft. It typically uses multi-rotor UAVs equipped with mechanical grippers, suction pumps, or negative pressure collection chambers to perform low-altitude hovering operations at specific coordinate points. By periodically activating the gripping device or suction component, the sediments are adsorbed or collected into the carrier container, realizing fixed-point sampling operations within the target area.

[0003] In current river sediment sampling processes, sampling is mainly carried out through fixed-point hovering and timed grabbing devices. The sampling trigger period cannot dynamically identify the disturbance state, and the sample collection relies on mechanical action to complete the task, ignoring the influence of airflow changes. In variable water environments, especially in areas with rapid river currents or sudden changes in flow velocity, the match between negative pressure absorption and sediment suspension state is low, which can easily lead to mixed sampling particles or particle sizes deviating from the target range. This results in a decrease in the accuracy of analytical data, interferes with the identification of sediment composition and the judgment of distribution trends, and affects the reliability of subsequent environmental monitoring and sample tracing results. Summary of the Invention

[0004] To address the technical problems existing in the prior art, this invention provides an intelligent sampling method for aquatic sediments using unmanned aerial vehicles (UAVs) based on vortex sorting, comprising the following steps:

[0005] To achieve the above objectives, the present invention adopts the following technical solution: an intelligent sampling method for sediments in aquatic systems based on vortex sorting using unmanned aerial vehicles (UAVs), comprising the following steps:

[0006] S1: Obtain the duct direction change sequence of the swirl sorting sampling head, the time period of disturbance occurrence and the deflection trajectory of the rectifier plate, count the number of disturbance direction changes and the abrupt change point of the rectifier plate angle, perform position mapping with the rectifier plate response area, and generate the rectification interference area delineation result;

[0007] S2: Based on the rectification interference region delineation results, identify the steady-state segment of air intake at the corresponding swirl inlet, mark the swirl inlet position, and generate swirl inlet stable section data;

[0008] S3: Based on the stable section data of the swirling inlet, collect the rotational velocity sequence in the swirling cavity, the mapping relationship between the guide angle setting value and the standard sedimentary particle density range, screen the screening interval boundary that the screen structure can be directly aligned with, and generate the sedimentary layer screening alignment interval.

[0009] S4: Based on the alignment interval of the sediment layer, determine whether the height of the screen enters the boundary of the target interval. If it is not within the boundary, perform the alignment operation and generate a screen alignment execution record.

[0010] S5: Based on the screen alignment execution record, identify the intersection of the current opening state of the rectifier plate and the screen action trigger time, record the rectification adjustment, screen action and negative pressure path status stage information, and generate a UAV water system sediment intelligent sampling record.

[0011] As a further aspect of the present invention, the rectification interference region delineation result includes the distribution of the number of direction changes, the location of the angle abrupt change point, and the mapping relationship of the interference region; the vortex inlet stable section data includes airflow direction stable section information, disturbance decay time, and the location of the steady-state segment of air intake; the sediment layer screening alignment interval includes the rotation speed interval, the guide angle interval, and the qualified screening boundary; the screen alignment execution record includes the screen height position, alignment direction status, and alignment holding time; and the UAV water system sediment intelligent sampling record includes the rectification adjustment time series, the screen action time series, and the negative pressure path status series.

[0012] As a further aspect of the present invention, the rotational speed sequence is specifically a sequence of critical settling rates of particles calculated according to the centrifugal settling formula.

[0013] As a further aspect of the present invention, the boundary of the screening interval is specifically the acceptable range of ±3% of the standard screen aperture tolerance.

[0014] As a further aspect of the present invention, the step of obtaining the rectification interference region delineation result specifically includes:

[0015] S111: Acquire the standard anemometer direction change sequence data set in the duct of the cyclone separator sampling head, the time period information of disturbance occurrence, and the time sequence trajectory of the rectifier deflection angle sensor, perform time alignment, count the continuous direction change points, change amplitude and the number of direction change points, and generate the number of disturbance direction changes.

[0016] S112: Based on the number of times the disturbance direction changes, perform a first-order slope calculation on the difference sequence of the rectifier deflection angle change value in each disturbance time period. Match the position of the corresponding direction change point with the change trend of the rectifier angle, extract all angle change points, and generate angle change point distribution data.

[0017] S113: Based on the angle mutation point distribution data and the response area division intervals divided by the rectifier plate structure, the angle mutation point location index is mapped to the corresponding response area number. The mutation point count results under each area number are summarized, and the number of the mapped disturbance segment sequence is collected in sequence according to the area number to generate the rectification interference area delineation result.

[0018] As a further aspect of the present invention, the step of acquiring data in the stable section of the swirl inlet specifically comprises:

[0019] S211: Based on the rectification interference area delineation results, read the wind speed direction sequence and wind speed amplitude sequence of each time period under the negative pressure path, extract the time sequence according to each disturbance period, and combine it with the rectifier plate angle change sequence to reorganize the time, determine the wind speed direction difference value and wind speed amplitude fluctuation range in the same interval, mark the stable airflow direction segment, and generate the airflow stable interval sequence.

[0020] S212: Based on the airflow stable interval sequence, combined with the rectifier plate opening and closing state signal sequence and the wind speed amplitude change sequence, locate the time period when the rectifier plate is not closed, and perform time-series statistics on the wind speed amplitude value sequence within the segment according to the continuous decreasing segment to obtain the continuous time distribution segment and generate the wind speed stable intake segment.

[0021] S213: Based on the wind speed stable intake section, according to the spatial arrangement coordinate data of the swirl inlet sensor, the airflow sensor number corresponding to each stable intake section is spatially indexed and converted to locate the duct coordinate section, the start and end times of each stable intake section are mapped and marked as swirl inlet segments, and swirl inlet stable section data is generated.

[0022] As a further aspect of the present invention, the step of obtaining the alignment interval for screening the deposition layer specifically comprises:

[0023] S311: After collecting the data of the stable section of the swirl inlet, obtain the particle rotation velocity sequence corresponding to each time node in the swirl cavity, calculate the critical settling rate of the particles at each time point rotation velocity, and analyze the settling velocity field of the particles at different radial positions to obtain particle settling velocity distribution data.

[0024] S312: Based on the particle settling velocity distribution data, read the guide angle setting value and the standard sedimentary particle density range, cut the velocity field under different rotation speeds according to the direction of the deflection force line formed by each guide angle, establish the sedimentary flow field sub-region under guide deflection, calculate and obtain the boundary value of the sedimentary path region formed by each guide angle, compare it with the standard sedimentary layer thickness threshold, screen out the path distribution segments that have not formed a layered structure, and generate sedimentary path layered intervals according to the remaining regions;

[0025] S313: Based on the layered intervals of the deposition path, the actual measured values ​​of the apertures of each sieve hole in the sieve structure are compared with the standard sieve tolerance range setting values. The layered path boundary intervals that meet the upper and lower limit envelope conditions of the sieve holes are extracted. The duration and number sequence are counted in all matching segments. The path boundaries that can be directly aligned are marked and collected. A numbered index table is established to generate the deposition layer screening alignment interval.

[0026] As a further aspect of the present invention, the step of obtaining the screen alignment execution record specifically comprises:

[0027] S411: Based on the layered interval of the deposition path, obtain the corresponding screen number, read the displacement record of the screen cylinder at each time node, compare the coordinate position in the displacement state data with the physical boundary range value of the corresponding section of the target interval, calculate the relative offset between the screen edge positioning point and the boundary start and end coordinates, and generate displacement alignment offset data.

[0028] S412: Based on the displacement alignment offset data, determine whether the current alignment direction of the screen is within the target range, analyze whether the coordinate difference between the bottom and top of the screen is completely within the boundary, and if it is not within the boundary, obtain the slide rail drive direction signal according to the offset direction flag, until the offset is zero, and obtain the screen boundary positioning determination result.

[0029] S413: Based on the screen boundary positioning determination result, start the time recorder for the current coordinate position when the screen is in position, collect the holding time of the screen from the last shift to the current stationary state, and record the corresponding slide rail number and coordinate number. Associate the time data with the screen number data and store them to generate a screen alignment execution record.

[0030] As a further aspect of the present invention, the steps for obtaining intelligent sampling and recording of aquatic sediments by unmanned aerial vehicles are specifically as follows:

[0031] S511: Based on the screen alignment execution record, extract the timestamp and screen number information of the screen trigger action, sequentially obtain the rectifier plate's open status flag bit and status timestamp at the corresponding time, determine whether there is a record in the same window where the rectifier plate status flag is in adjustment, and if so, mark the corresponding screen number as being in an interference state within the time period, and generate a rectifier cross-interference mark record.

[0032] S512: Extract the corresponding screen number in the marked section according to the rectifier cross interference mark record, detect whether the state after each alignment is completed is paused, record the end time when the last state flag of the screen is invalid, if the rectifier plate state sequence shows a fully open state, record the corresponding timestamp and bind the screen number, and obtain the screen unlock timestamp.

[0033] S513: Based on the screen unlocking timestamp as the time base point, read all action records after the corresponding time point under the corresponding screen number in sequence, extract the rectifier plate state change sequence and the negative pressure path on / off state sequence, arrange the record items in chronological order, and generate UAV water system sediment intelligent sampling record.

[0034] A drone-based intelligent sediment sampling system for aquatic systems, based on cyclone sorting, includes:

[0035] The wind speed disturbance identification module is used to perform S1: acquire the duct direction change sequence of the swirl sorting sampling head, the time period of disturbance occurrence and the deflection trajectory of the rectifier plate, count the number of disturbance direction changes and the abrupt change point of the rectifier plate angle, perform position mapping with the rectifier plate response area, and generate the rectification interference area delineation result;

[0036] The stable path determination module is used to perform S2: based on the rectification interference region delineation result, identify the steady-state segment of air intake at the corresponding vortex inlet, mark the vortex inlet position, and generate vortex inlet stable section data;

[0037] The sedimentation interval positioning module is used to perform S3: based on the stable section data of the vortex inlet, it collects the rotation speed sequence in the vortex cavity, the mapping relationship between the guide angle setting value and the standard sedimentation particle density interval, and filters the screening interval boundary that the screen structure can be directly aligned with to generate the sedimentation layer screening alignment interval.

[0038] The screen path control module is used to execute S4: based on the screening alignment interval of the deposition layer, determine whether the height of the screen is within the boundary of the target interval. If it is not within the boundary, perform the alignment operation and generate a screen alignment execution record.

[0039] The linkage process recording module is used to execute S5: based on the screen alignment execution record, identify the intersection of the current opening state of the rectifier plate and the screen action trigger time, record the rectification adjustment, screen action and negative pressure path status stage information, and generate a UAV water system sediment intelligent sampling record.

[0040] Compared with the prior art, the advantages and positive effects of the present invention are as follows:

[0041] In this invention, a stable section calibration is formed by superimposing wind speed direction fluctuations and rectifier plate trajectory changes. By combining multi-parameter mapping of rotation speed and particle density, the screening range is locked to the alignment interval. The sieve captures the motion state of sediments in the sediment layer, and the entire process sampling sequence is constructed by the coordinated timing of rectification action and sieve operation. This can dynamically extract the disturbance characteristics of real water bodies, match the motion law of sediments, improve the accuracy of sampling trigger response, and enhance the screening alignment accuracy under the coupling of multiple factors. It can accurately capture the target section under the interference of airflow disturbance and particle settling process, stably maintain the particle layer structure, and synchronously record the behavior of each stage of the sampling process. Attached Figure Description

[0042] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying 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.

[0043] Figure 1 This is a schematic diagram of the steps of the present invention;

[0044] Figure 2 A flowchart illustrating the process of obtaining the rectification interference region delineation results of this invention;

[0045] Figure 3 This is a flowchart illustrating the acquisition of stable section data at the vortex inlet in this invention.

[0046] Figure 4 This is a flowchart of the process for obtaining the alignment interval for screening the deposition layer in this invention;

[0047] Figure 5 This is a flowchart illustrating the process of obtaining the screen alignment execution record according to the present invention.

[0048] Figure 6 This is a flowchart illustrating the process of acquiring intelligent sampling records of aquatic sediments using an unmanned aerial vehicle (UAV) according to the present invention. Detailed Implementation

[0049] The technical solution of the present invention will now be described with reference to the accompanying drawings.

[0050] In embodiments of the present invention, words such as "exemplarily," "for example," etc., are used to indicate that something is an example, illustration, or description. Any embodiment or design described as "exemplary" in the present invention should not be construed as being more preferred or advantageous than other embodiments or designs. Specifically, the use of the word "exemplary" is intended to present the concept in a concrete manner. Furthermore, in embodiments of the present invention, the meaning expressed by "and / or" can be both, or either one.

[0051] In the embodiments of this invention, the terms "image" and "picture" may sometimes be used interchangeably. It should be noted that, without emphasizing the distinction between them, their intended meanings are consistent. Similarly, the terms "of," "corresponding (relevant)," and "corresponding" may sometimes be used interchangeably. It should be noted that, without emphasizing the distinction between them, their intended meanings are consistent.

[0052] In this embodiment of the invention, sometimes a subscript such as W1 may be written in a non-subscript form such as W1. When the difference is not emphasized, the meaning they express is the same.

[0053] To make the technical problems, technical solutions and advantages of the present invention clearer, a detailed description will be given below in conjunction with the accompanying drawings and specific embodiments.

[0054] Please see Figure 1 This invention provides an intelligent sampling method for unmanned aerial vehicle (UAV) sediments based on vortex sorting, comprising the following steps:

[0055] S1: Obtain the sequence of changes in the direction of the standard anemometer in the duct of the swirl sorting sampling head, the time period of disturbance occurrence, and the trajectory of the rectifier deflection angle sensor. Calculate the number of changes in the direction of disturbance and the distribution of the corresponding rectifier angle mutation points. Map the positions of these points to the rectifier response area to generate the result of the rectification interference area delineation.

[0056] S2: Based on the results of the rectification interference area delineation, the stable section of airflow direction and the time period of disturbance attenuation in the negative pressure path are statistically analyzed. Combined with the continuous time distribution of the period when the rectifier plate is not closed and the area where the wind speed amplitude decreases, the steady-state segment of air intake at the corresponding swirl inlet is identified, and the swirl inlet position is marked to generate swirl inlet stable section data.

[0057] S3: Based on the stable section data of the vortex inlet, collect the rotational velocity sequence in the vortex cavity (critical settling velocity of particles calculated according to the ISO 13318-2 centrifugal sedimentation formula), the mapping relationship between the guide angle setting value and the standard sedimentary particle density range, and layer the sedimentation path according to the fluid deflection zone formed by the rotational velocity and the guide angle. Screen the screening interval boundary that the screen structure can be directly aligned with (the qualified range of standard screen aperture tolerance ±3%) to generate the sedimentation layer screening alignment interval.

[0058] S4: Based on the sediment layer screening alignment interval, obtain the displacement status data and alignment direction status of the current screen cylinder along the slide rail, determine whether the height of the screen has entered the target interval boundary, if not within the boundary, drive the slide rail to perform displacement and mark the position holding time after alignment, and generate the screen alignment execution record;

[0059] S5: Based on the screen alignment execution record, identify the intersection of the current opening state of the rectifier plate and the screen action trigger time. When the rectifier is in the interference adjustment state, mark the screen action as paused. When the rectifier plate is reopened, record the screen unlock trigger time. Record the information of each stage of rectifier adjustment, screen action and negative pressure path status in chronological order to generate a UAV water system sediment intelligent sampling record.

[0060] The rectification interference area delineation results include the distribution of the number of direction changes, the location of the angle abrupt change point, and the mapping relationship of the interference area. The stable section data of the vortex inlet includes information on the stable section of airflow direction, the disturbance decay time, and the location of the steady-state segment of air intake. The sediment layer screening alignment interval includes the rotation speed interval, the guide angle interval, and the qualified screening boundary. The screen alignment execution record includes the screen height position, alignment direction status, and alignment holding time. The UAV water system sediment intelligent sampling record includes the rectification adjustment time series, the screen action time series, and the negative pressure path status series.

[0061] Please see Figure 2 The specific steps of S1 are as follows:

[0062] S111: Acquire the standard anemometer direction change sequence data set in the duct of the cyclone separator sampling head, the time period information of disturbance occurrence, and the time sequence trajectory of the rectifier deflection angle sensor, perform time alignment, count the continuous direction change points, change amplitude and the number of direction change points, and generate the number of disturbance direction changes.

[0063] To acquire the sequence data of direction changes from standard anemometers installed within the duct of the cyclone separator sampling head, the time periods of disturbance occurrence, and the time series trajectory of the rectifier deflection angle sensor, it is necessary to first extract the wind speed direction values ​​collected by each of the multiple anemometers deployed at different locations on the duct cross-section. The wind speed direction is recorded in angular form, and the sampling frequency is set to 10Hz per second. The corresponding disturbance time periods can be identified by observing that the sudden change in wind speed direction exceeds a preset disturbance identification threshold. The disturbance identification threshold is set when the direction change exceeds 20° within 3 seconds, i.e., when there is a cumulative direction change exceeding 20° in 30 consecutive sampling points. A data segment of 20° is considered a disturbance segment. By combining this condition and traversing the entire anemometer data sequence, the start and end times of all disturbance segments can be marked. For example, the first disturbance segment lasts from 15.2 seconds to 18.7 seconds, a total of 3.5 seconds; this segment will serve as the reference for subsequent correlation. For the rectifier deflection angle sensor trajectory, the angle value changes within the same time range are extracted, with the sampling frequency set to 10Hz. Time alignment is performed on all disturbance segments, i.e., the corresponding time intervals of wind speed direction data and deflection angle data are extracted. Within the identified disturbance segments, differential processing is performed based on the direction change value within each second, with the differential formula being Δθ. i =θ i -θ i-1θ i Let Δθ represent the wind speed direction angle value at time i. i A change in direction of more than 10° is counted as one point of change. For example, if the Δθ sequence in a certain segment is [2, 4, 12, 15, 3], the 3rd and 4th points are the points of change. If there are a total of 2 changes in direction, then the number of changes in the direction of the disturbance in this segment is 2. All disturbance segments are processed in this way and the number of points of change in direction in each disturbance segment is counted to finally obtain the number of changes in the direction of the disturbance.

[0064] S112: Based on the number of times the disturbance direction changes, the first-order slope is calculated for the difference sequence of the rectifier deflection angle change value in each disturbance time period. The position of the corresponding direction change point at the time is matched with the change trend of the rectifier angle. All angle change points are extracted to generate angle change point distribution data.

[0065] Based on the number of times the disturbance direction changes, it is necessary to further retrieve the rectifier deflection angle sensor trajectory within the corresponding disturbance segment, and perform differential processing on the deflection angle change trend in each disturbance segment, that is, calculate the angle change between any two adjacent points, using Δα. i =α i -α i-1 Formula, where α iThis represents the rectifier plate angle value at the i-th sampling time. Subsequently, the slope change in the continuous Δα sequence is calculated. If the slope suddenly increases between two consecutive points, meaning the difference in Δα values ​​between two consecutive time periods exceeds the slope change threshold, it is identified as an angle abrupt change point. This slope abrupt increase threshold is set to 5° / s. The basis for this setting is that the natural response amplitude of the rectifier plate under steady-state airflow disturbances typically does not exceed 3° per second. Within the disturbance range where the anemometer direction change amplitude is greater than 20°, the maximum rate of change of the rectifier plate's deflection response is typically measured to be between 2.5° / s and 4.7° / s. Therefore, when the angle change slope exceeds 5° / s in any sampling interval, it can be considered an abnormal fluctuation in the non-inertial response driven by wind direction disturbance. This value tends to rise slightly with the stiffness of the rectifier plate material and the shortening of the sensor sampling interval. The sampling frequency is increased to 2... At 0Hz, the threshold can be increased to 6.2° / s. At 10Hz, 5° / s is used as the upper limit for steady-state benchmark identification. For example, if the Δα sequence is [1, 2, 8, 1], then point 3 is the mutation point. The mutation point index is mapped to the relative time position within the disturbance segment and matched with the position of the disturbance direction change point obtained in the previous step. If the time difference between a mutation point and the direction change point is less than 0.5 seconds, the correlation is considered to be valid, forming the rectifier plate mutation response relationship driven by the direction disturbance. All disturbance segments are traversed and the position of the angle change point that meets the mutation judgment criteria in each segment is counted. The index of the mutation point is recorded according to the time position. For example, in the first disturbance segment, the mutation points appear 1.6 seconds and 2.9 seconds after the start of the disturbance, and the corresponding sampling points are point 16 and point 29. Finally, the angle mutation point distribution data is generated.

[0066] S113: Based on the distribution data of angle mutation points, combined with the response area division intervals divided by the rectifier plate structure, the position index of the angle mutation point is mapped to the corresponding response area number. The mutation point count results under each area number are summarized, and the number of the mapped disturbance segment sequence is collected in order according to the area number to generate the rectification interference area delineation result.

[0067] Based on the distribution data of angle abrupt change points, the response region interval values ​​set by the rectifier structure are invoked. The rectifier is divided into several numbered regions on the duct section, each region being 0.1m in length, resulting in 10 regions arranged sequentially from number 1 to 10. According to the mapping relationship between the spatial location of the rectifier deflection angle sensor's measuring point and the numbered regions, for example, sensor A installed at 0.15m corresponds to region number 2. When an abrupt change point occurs at this location, it is counted in the statistics for region number 2. The spatial coordinates of the abrupt change point location indices identified in all disturbance segments are converted using the conversion formula X. i = L×(i / N), where L is the total length of the rectifier board, N is the total number of sampling points, and i is the index of the mutation point. For example, if a mutation point is at the 30th sampling point, L = 1m, N = 100, then X i=0.3m, corresponding to region 4; map all the coordinates of the mutation points to the corresponding response region number in sequence, and record the number of mutation points contained in each numbered region. Then, statistically collect them according to the region number from 1 to 10, and finally form a matrix of the number of mutation points in each region of the rectifier board under all disturbance segments, and obtain the result of the rectifier interference region delineation.

[0068] Please see Figure 3 The specific steps of S2 are as follows:

[0069] S211: Based on the results of the rectification interference area delineation, read the wind speed direction sequence and wind speed amplitude sequence of each time period under the negative pressure path, extract the time sequence according to each disturbance period, and combine it with the rectifier plate angle change sequence to reorganize the time, determine the wind speed direction difference value and wind speed amplitude fluctuation range in the same interval, mark the stable airflow direction segment, and generate the airflow stable interval sequence.

[0070] Based on the results of the rectification interference area delineation, the wind speed direction sequence and wind speed amplitude sequence for each time period under the negative pressure path are called. In the operation of extracting the time sequence according to each disturbance period, the start and end times of the corresponding time period for each rectification interference area are first extracted. Then, the wind speed direction data θ(t) and wind speed amplitude data V(t) for the same time interval are extracted from the anemometer data recorded in the negative pressure channel. θ(t) is represented in °, and V(t) is recorded in m / s. The sampling frequency is set to 20Hz per second. The rectifier plate angle change sequence α(t) is extracted simultaneously. Differential processing is performed on θ(t) in each time period, i.e., Δθ i =θ i -θ i-1 If the variation of Δθ within 5 consecutive sampling points is within ±3°, then the segment is considered directionally stable. For example, if Δθ = [2.1, 1.7, 2.5, 0.9, 1.2] within t = 4s to t = 4.25s, the stability criterion is met. Simultaneously, the amplitude difference ΔV = max(V) is calculated for V(t) within the same interval. t )-min(V t If ΔV is less than 0.15 m / s, it is determined to be a stable wind speed section. For example, a section with V = [1.92, 2.01, 1.97, 2.00, 1.96] and an amplitude of 0.09 m / s meets the wind speed stability requirement. After the disturbance section ends, if the wind speed continues to decrease for 0.5 seconds, the differential ΔV is used. i =V i -V i-1 If continuous ΔV i If all values ​​are negative and there is no reverse growth point, it is judged as a disturbance attenuation segment. Finally, by combining the directional stability and amplitude stability markers, the time period is integrated into a wind speed stability interval sequence, and the airflow stability interval sequence is obtained.

[0071] S212: Based on the airflow stable interval sequence, combined with the rectifier plate opening and closing status signal sequence and the wind speed amplitude change sequence, locate the time period when the rectifier plate is not closed, and perform time-series statistics on the wind speed amplitude value sequence within the segment according to the continuous decreasing segment to obtain the continuous time distribution segment and generate the wind speed stable intake segment.

[0072] Based on the airflow stability interval sequence, when calling the rectifier plate opening / closing state signal sequence and the wind speed amplitude change sequence, the corresponding time sequence α is first extracted from the rectifier plate control signal. s (t), where state 1 represents a closed loop and state 0 represents an open loop, for the entire stable airflow range α s (t) is used for filtering to extract α. s The time interval from t(t) = 0 is considered the unclosed section of the rectifier plate. For example, the rectifier plate remains unclosed between t = 6.2s and t = 8.7s. Within this unclosed section, a sliding window is used to statistically analyze the wind speed amplitude V(t), with a window length of 1 second and a sampling frequency of 20Hz. The amplitude ΔV = max(V(t)) within each window is calculated. t )-min(V t And determine the mean difference ΔV between two consecutive windows. - Whether it continues to decrease, if ΔV - If the change between two consecutive windows is greater than 0.25 m / s and the duration of the decrease exceeds 1.2 seconds, it is considered a region of decreasing amplitude. For example, if the mean value of V(t) decreases from 2.5 m / s to 2.2 m / s within the interval t = 7.0 s to t = 8.4 s, then ΔV - =0.3m / s, which meets the judgment condition; then the intersection of the marked amplitude reduction time period and the time period in the airflow stable interval sequence is screened, the intersection time range is extracted to form a continuous inhalation period, and the period is numbered according to the inhalation continuity to obtain the wind speed stable inhalation section.

[0073] S213: Based on the wind speed stable intake section, according to the spatial arrangement coordinate data of the swirl inlet sensor, the spatial index conversion of the airflow sensor number corresponding to each stable intake section is performed to locate the duct coordinate section, the start and end time of each stable intake section is mapped and marked as the swirl inlet segment, and the swirl inlet stable section data is generated.

[0074] Based on the wind speed stable intake section, the spatial arrangement coordinate data X of the swirl inlet sensor is retrieved. i With Y iSpatial alignment is performed by first extracting the spatial coordinates of each sensor number from the sensor layout table at the vortex inlet. For example, sensor number S1 corresponds to X1 = 0.25m and Y1 = 0.40m. A spatial location mapping table is then established sequentially. Coordinate index matching is performed on the sensor numbers involved in each wind speed stable intake section to locate their duct location area. For example, if S1, S2, and S3 are in this intake section, the corresponding inlet is in the range of 0.2m to 0.5m. Next, the time range of each intake section is registered. For example, the first section starts at t = 10.0s and ends at t = 12.8s. This section is then bound to the corresponding inlet coordinate range to complete the spatiotemporal pairing. The pairing results of each section are organized according to the number sequence to establish a stable section number table. Finally, a set of stable sections after all intake sections are aligned with the spatial inlet points is formed, generating vortex inlet stable section data.

[0075] Please see Figure 4 The specific steps of S3 are as follows:

[0076] S311: After collecting data from the stable section of the swirl inlet, obtain the particle rotation velocity sequence corresponding to each time node in the swirl chamber, calculate the critical settling velocity of the particles at each time point, and analyze the settling velocity field of the particles at different radial positions to obtain particle settling velocity distribution data.

[0077] After collecting data from the stable section of the cyclone inlet, the particle rotation velocity sequence V is extracted according to the corresponding number of each inlet section. p (t), the extraction time interval is 10.0 seconds to 14.0 seconds, the sampling interval is 0.02 seconds, and the particle rotation speed is monitored in real time by a velocity sensor deployed in the radial direction of the rotation cavity. For example, in the segment i=1, the particle rotation speed is The velocity in section i=2 is 2.7 m / s, and the velocity in section i=3 is 3.5 m / s, corresponding to the particle size dp. i The measured values ​​obtained using the optical diameter measuring module were 38 μm, 45 μm, and 40 μm, respectively, which, after conversion to meters, are 3.8 × 10⁻⁶. -5 m, 4.5×10 -5 m and 4.0×10 -5 m, the viscosity η of the medium was measured at 25℃ and set to 0.0012 Pa·s, and the particle density was measured to be 2650 kg / m³. 3 The density of the medium is 1025 kg / m³ 3 The density difference Δρ is obtained. p =1625kg / m 3 Based on the above values, the settlement velocity is calculated using the following formula:

[0078]

[0079] Taking segment i=1 as an example, substitute the data:

[0080]

[0081] Similarly, calculate i=2 and i=3:

[0082]

[0083] The results for each segment are recorded as follows:

[0084] Table 1. Calculation of Particle Settling Velocity

[0085]

[0086]

[0087] As shown in Table 1, by combining particle size and rotation speed, the settling velocity of each segment of particles under centrifugal settling environment is obtained, providing a velocity benchmark for subsequent path thickness calculation, and finally obtaining particle settling velocity distribution data.

[0088] S312: Based on the particle settling velocity distribution data, read the guide angle setting value and the standard sedimentary particle density range. According to the direction of the deflection force line formed by each guide angle, the velocity field at different rotational speeds is cut along the angular direction to establish a sub-region of the sedimentary flow field under guide deflection, using the formula:

[0089]

[0090] The boundary value of the depositional path region formed by each diversion angle is calculated and compared with the standard depositional layer thickness threshold. Path segments that do not form a stratified structure are filtered out, and depositional path stratification intervals are generated according to the remaining regions, where ΔZ i Indicates the thickness of the deposition path in the i-th segment. Represents the particle rotation speed [L·T] -1 ], L i The value [L] represents the path length within the vortex region. The settling velocity of particles in the direction of gravity [L·T] -1 The particle density, medium density, and particle size are calculated using the formula derived from ISO 13318-2.

[0091] Based on the particle settling velocity distribution data, the guide angle setting value θ is invoked. a With particle density range ρ st The angle value is set from 20° to 55°. The path deflection segment under different angles is recorded at 5° intervals. For each deflection path, the length L from the vortex inlet to the center of the guide surface is measured. iThe depths are 0.18m, 0.22m, and 0.16m, respectively. The boundary values ​​of the depositional path are calculated segment by segment according to the formula, as follows:

[0092]

[0093] Table 2 Calculation of Depositional Path Boundary

[0094]

[0095]

[0096] As shown in Table 2, the path boundary values ​​are much larger than the standard threshold for the size of the sedimentary structure, so further screening is required to generate sedimentary path stratification intervals.

[0097] The boundary value of the deposition path region refers to the maximum radial or axial extension of the deposition area formed by particles moving along the guide direction after being driven by rotation and gravity settling in the vortex cavity. This value reflects the farthest spatial position that particles may eventually deposit under given rotation speed, settling speed, and structural path length. Its physical meaning is to describe the upper limit of the path that particles travel before migrating to a stable position in the flow field. It is a core indicator for delineating the particle stratification deposition interface, matching the screen structure size, and controlling the sorting accuracy. This boundary value is directly controlled by the tangential velocity of the particles, the settling duration, and the geometric characteristics of the guide channel. Therefore, in engineering applications, it is often used to determine whether particles in a certain section can complete effective deposition within the allowable range of the structure and to provide a spatial parameter basis for the subsequent structural layout of the screening device.

[0098] formula The computational logic is based on the spatial displacement behavior of particles within a swirling cavity under the influence of a centrifugal field. The structural relationship in this expression can be decomposed into a combination of physical meanings of "velocity × time," where... This represents the settling time of a particle in the direction of gravity from the inlet to the center of the guide surface, i.e., over a path length L. i Under fixed conditions, the lower the settling velocity, the longer the particles remain in that section. This increased residence time results in a greater displacement of the particles in the direction of rotation. The particle rotation velocity... Since the offset length is directly proportional, a multiplicative method is used to couple the lateral rotation velocity and the longitudinal settling time to obtain the deposition path thickness ΔZ formed by the particles in the current structural path. i This expresses the combined effect of horizontal migration caused by rotational speed and the dominance time of settlement in two-dimensional offset behavior.

[0099] S313: Based on the sedimentation path layering interval, the actual measured value of each sieve aperture in the sieve structure is compared with the standard sieve tolerance range setting value to extract the layering path boundary interval that meets the upper and lower limit envelope conditions of the sieve aperture. The duration and number sequence are counted in all matching segments. The path boundaries that can be directly aligned are marked and collected, a number index table is established, and the sedimentation layer screening alignment interval is generated.

[0100] Based on the stratified intervals of the deposition path, the sieve aperture specification A of the sieve structure is called. s =0.6m, its acceptable range is A s ±3%=[0.582,0.618]m,set the path boundary ΔZ i Screening revealed that the thicknesses of all three path segments exceeded the maximum allowable range of the screen (344.89 m, 262.85 m, and 296.31 m, respectively). Therefore, under the current guide angle setting and rotation speed combination, all path thicknesses exceeded the screen tolerance limit, and no matching segments could be directly screened. This situation requires subsequent adjustments to the structural parameters using deceleration or diameter reduction control strategies. Since no matching segments were found in the current round, no number was generated for archiving, the record is empty, and the generated deposition layer screening alignment interval is an empty set. This result indicates that under the current combination of particle density, particle size, and guide configuration, the resulting deposition thickness is too thick and unsuitable for the current screen. Adjustments to the rotation speed or fluid shear mechanism are needed to reconfigure the path design.

[0101] Please see Figure 5 The specific steps of S4 are as follows:

[0102] S411: Obtain the corresponding screen number based on the sedimentation path layered interval, read the displacement record of the screen cylinder at each time node, compare the coordinate position in the displacement state data with the physical boundary range value of the corresponding section of the target interval, calculate the relative offset between the screen edge positioning point and the boundary start and end coordinates, and generate displacement alignment offset data.

[0103] After obtaining the corresponding screen number based on the sedimentation path stratification interval, the unique identifier of the screen cylinder at the start of the operation is obtained and bound one-to-one with the marked sedimentation path numbers. The track coordinate values ​​recorded by the displacement sensor in the track control unit are called, and the absolute displacement value and displacement direction flag at each time point are read. The reading frequency is 50Hz, and the positioning accuracy is set to 0.01m. The coordinate value under each screen number is compared with the boundary coordinates of its corresponding sedimentation path interval. The boundary coordinates are determined by the upper limit Z... max With lower limit Z min This indicates that the value range is set by the filtering interval formed in the previous main step. For example, the boundary corresponding to screen number A is Z. max =1.80m, Z min=1.42m, the current coordinate value of the screen slide rail is Z s =1.38m, the calculated offset is ΔZ = Z min -Z s =0.04m, this difference indicates that the screen has not yet entered the interval and needs to continue moving. The direction of the offset is determined by the sign of the current slide rail speed. If v s If the value is greater than 0, the shift is upward; otherwise, the shift is downward. After each sampling, the difference is updated and iterated to the next time point. All displacement record time periods that are not within the interval are filtered out. The screen coordinate values ​​and boundary difference sequences are extracted to form an array. Finally, the set of differences between the screen cylinder and the target boundary at each time point is calculated to obtain the displacement alignment offset data.

[0104] S412: Based on the displacement alignment offset data, determine whether the current alignment direction of the screen is within the target range, analyze whether the coordinate difference between the bottom and top of the screen is completely within the boundary. If it is not within the boundary, obtain the slide rail drive direction signal according to the offset direction flag, until the offset is zero, and obtain the screen boundary positioning determination result.

[0105] Based on the displacement alignment offset data, the sign of the difference is first extracted to determine whether the current movement direction of the screen is consistent with the interval approximation direction. The judgment benchmark is set as the Z coordinate of the bottom of the screen. b With top coordinate Z t Z b =Z s Z t =Z s +H s H s =0.38m is the height of the screen structure, and the interval boundary is set as Z. min =1.42m, Z max =1.80m, the judgment condition is Z b ≥Z min And Z t ≤Z max If the determination is negative, the ΔZ value from the previous sub-step is retrieved and the direction flag is read. If the flag is negative, a downward movement instruction is initiated; otherwise, it moves upward. The driver's increment value is set to 0.005 m / step to gradually adjust the screen position. The Z value is reacquired after each movement. b Z t The process is repeated, with a maximum of 200 iterations, or until all conditions are met simultaneously. For example, initial Z... s =1.38m, then Z t =1.76m, this range overlaps with the interval boundary but does not completely contain it, therefore it needs to be moved upwards to complete the process to Z. s When the value is 1.42m, the condition is met, the iteration terminates, and the result of the screen boundary positioning determination is obtained.

[0106] S413: Based on the screen boundary positioning determination result, when the screen is in position, start the time recorder for the current coordinate position, collect the holding time of the screen from the last shift to the current stationary state, and record the corresponding slide rail number and coordinate number. Store the time data and screen number data together to generate the screen alignment execution record.

[0107] The result of the screen boundary positioning determination is used as the basis for the judgment. When the screen is stationary, the position recorder is activated to record the current slide rail coordinate Z. s The screen number and recording timestamp are written to the buffer. If the displacement change is less than 0.001m in 20 consecutive records, the stationary state is determined, the holding time recording module is activated, and the stationary start time T0 is recorded. The system checks the slide rail status at 1s intervals. If the slide rail coordinate difference is still less than 0.001m in subsequent consecutive cycles, the time record is accumulated. Let's assume that the slide rail remains stable until T0. end =T0+15s, the record holding time is 15 seconds, and it is written to the trajectory log file together with the current screen number and coordinate data. Finally, the screen number, static start time, holding time, and alignment coordinates are combined to form the record data and generate the screen alignment execution record.

[0108] Please see Figure 6 The specific steps of S5 are as follows:

[0109] S511: Based on the screen alignment execution record, extract the timestamp and screen number information of the screen trigger action, sequentially obtain the rectifier plate's on status flag and status timestamp at the corresponding time, determine whether there is a record in the same window where the rectifier plate status flag is in adjustment, and if so, mark the corresponding screen number as being in an interference state within the time period, and generate a rectifier cross-interference mark record.

[0110] Based on the screen alignment execution records, the screen number, action start time, and alignment completion time are extracted from each record. The status flag sequence of the rectifier control module within the same time period is obtained. Rectifier status data within 5 seconds before and after each screen action time period is filtered, and this recognition window is set to T. s -5s to T e +5s, where T s T is the start time of the screening action. eFor the end time of the screen action, extract the rectifier plate status flag value within this window. The status value is a Boolean type, with 1 indicating that the rectifier is in interference adjustment state and 0 indicating normal operation. If any record within this time window has a status value of 1, it is determined that the screen action is affected by rectification. The identification criteria are set as follows: screen number A, action start time 13:10:25, action end time 13:10:34, rectifier plate status value is 1 during the time period from 13:10:29 to 13:10:33, the determination result is "cross-interference exists". The comparison and determination logic is the judgment array [S ti If the value 1 is present in the flag table, write 1 to the flag table; otherwise, write 0. Record the correspondence between the screen number and the interference judgment result, and obtain the rectification cross-interference mark record.

[0111] S512: Extract the corresponding screen number in the marked section according to the rectifier cross interference mark record, detect whether the state is paused after each alignment is completed, record the end time when the last state flag of the screen is invalid, if the rectifier plate state sequence shows a fully open state, record the corresponding timestamp and bind the screen number, and obtain the screen unlock timestamp.

[0112] Based on the rectification cross-interference marker records, extract the screen numbers marked as having cross-interference. Obtain the corresponding action command sequence and track motion status data from the screen alignment control log. Identify the time period when the command status is invalid as the action pause segment. The criterion for judging the pause state is that the screen coordinates remain unchanged in two consecutive time records and the control signal is in the "empty command" state. Suppose that the track position of screen number B remains at 1.62m between 13:20:15 and 13:20:34, and the alignment control signal record is empty, it is judged as a pause state. Record the end time of this time period as the screen pause end time. Then extract the record time of all status flag values ​​of 0 in the rectifier plate status change sequence. Find the first rectification status record with a time greater than the pause end time. Let its timestamp be 13:20:42. Record this time as the trigger point for the screen action recovery state. The screen number and this timestamp form a key value group to obtain the screen unlock timestamp.

[0113] S513: Based on the screen unlocking timestamp as the time base point, read all action records after the corresponding time point under the corresponding screen number in sequence, extract the rectifier plate state change sequence and the negative pressure path on / off state sequence, arrange the record items in chronological order, and generate UAV water system sediment intelligent sampling record.

[0114] Using the screen unlock timestamp as the time base, all state change records in the rectifier plate control system are read, and the screen track control log and negative pressure suction path control log are extracted simultaneously. Assuming the unlock time is 13:20:42, all operation time records after 13:20:42 are extracted sequentially. The screen track control records that the screen moved at 13:20:44 and issued a locking command at 13:20:48. The rectifier control records a state switch to "adjustment" at 13:20:46, and the negative pressure path control records a negative pressure on / off signal at 13:20:49, set to "path open." The three data items are sorted by time from smallest to largest, and the merged fields include: timestamp, device module, state type, and action description. The sorted sequence number is recorded and bound to the screen number, then written to the database. A complete sampling process time trajectory sequence is established, generating a UAV-based intelligent sampling record for aquatic sediments.

[0115] A drone-based intelligent sediment sampling system for aquatic systems, based on cyclone sorting, includes:

[0116] The wind speed disturbance identification module is used to perform S1: acquire the duct direction change sequence of the swirl sorting sampling head, the time period of disturbance occurrence and the deflection trajectory of the rectifier plate, count the number of disturbance direction changes and the abrupt change point of the rectifier plate angle, perform position mapping with the rectifier plate response area, and generate the rectification interference area delineation result;

[0117] The stable path determination module is used to execute S2: based on the rectification interference region delineation results, it identifies the steady-state segment of air intake at the corresponding swirl inlet, marks the swirl inlet position, and generates swirl inlet stable section data;

[0118] The sedimentation interval positioning module is used to execute S3: Based on the stable section data of the vortex inlet, it collects the rotational velocity sequence in the vortex cavity, the mapping relationship between the guide angle setting value and the standard sedimentary particle density interval, and filters the screening interval boundaries that can be directly aligned with the screen structure to generate the sedimentation layer screening alignment interval.

[0119] The screen path control module is used to execute S4: based on the sediment layer screening alignment interval, determine whether the height of the screen is within the target interval boundary. If it is not within the boundary, perform the alignment operation and generate a screen alignment execution record.

[0120] The linkage process recording module is used to execute S5: based on the screen alignment execution record, it identifies the intersection of the current opening state of the rectifier plate and the screen action trigger time, records the rectification adjustment, screen action and negative pressure path status stage information, and generates a UAV water system sediment intelligent sampling record.

[0121] The above description is merely a specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the technical scope disclosed in the present invention should be included within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be determined by the scope of the claims.

Claims

1. An unmanned aerial vehicle (UAV) water system sediment intelligent sampling method based on cyclone sorting, characterized in that, The method comprises the following steps: S1: Obtain the direction change sequence of the cyclone sorting sampling head, the disturbance occurrence time period, and the deflection trajectory of the rectifier plate, count the number of direction changes and the angle mutation points of the rectifier plate, map the positions with the response area of the rectifier plate, and generate the rectification interference area demarcation result; S2: Based on the rectification interference area demarcation result, identify the air suction steady-state segment at the cyclone inlet, and mark the position of the cyclone inlet, to generate the cyclone inlet stable section data; S3: Based on the cyclone inlet stable section data, collect the rotation speed sequence in the cyclone cavity, the guide angle setting value, and the standard deposition particle density interval mapping relationship, filter the screen interval boundary that the screen structure can directly align, and generate the deposition layer screening alignment interval; S4: According to the deposition layer screening alignment interval, judge whether the height of the screen is in the target interval boundary, if not in the boundary, execute the alignment operation, and generate the screen alignment execution record; S5: Based on the screen alignment execution record, identify the intersection of the current opening state of the rectifier plate and the screen action trigger time, record the rectification adjustment, screen action, and negative pressure path state stage information, and generate the unmanned aerial vehicle water system sediment intelligent sampling record.

2. The cyclonic sorting based unmanned aerial vehicle water system sediment intelligent sampling method according to claim 1, characterized in that, The rectification interference area demarcation result includes the number of direction changes, the angle mutation point position, and the interference area mapping relationship. The cyclone inlet stable section data includes the airflow direction stable segment information, the disturbance decay time, and the air suction steady-state segment position. The deposition layer screening alignment interval includes the rotation speed interval, the guide angle interval, and the qualified screening boundary. The screen alignment execution record includes the screen height position, the alignment direction state, and the alignment holding time. The unmanned aerial vehicle water system sediment intelligent sampling record includes the rectification adjustment time sequence, the screen action time sequence, and the negative pressure path state sequence.

3. The cyclone separation based unmanned aerial vehicle water system sediment intelligent sampling method according to claim 1, characterized in that, The rotation speed sequence is specifically the critical particle settling rate sequence calculated according to the centrifugal settling formula.

4. The cyclonic sorting based unmanned aerial vehicle water system sediment intelligent sampling method according to claim 1, characterized in that, The screening interval boundary is specifically the qualified range of the standard screen aperture tolerance ± 3%.

5. The cyclonic sorting based unmanned aerial vehicle water system sediment intelligent sampling method according to claim 1, characterized in that, The rectification interference area demarcation result acquisition step specifically comprises: S111: Obtain the standard anemometer direction change sequence data, the disturbance occurrence time period information, and the time sequence trajectory of the rectifier plate deflection angle sensor set in the cyclone sorting sampling head, perform time alignment, count the continuous direction change points, the change amplitude, and the number of direction change points, and generate the number of disturbance direction changes; S112: According to the number of disturbance direction changes, calculate the first-order slope of the difference sequence of the rectifier plate deflection angle change value in each disturbance time period, match the change trend of the rectifier plate angle at the time position of the corresponding direction change point, extract all angle change points, and generate the angle mutation point distribution data; S113: Based on the angle mutation point distribution data, combine the response area division interval divided by the rectifier plate structure, index map the angle mutation point position to the number of the corresponding response area, count the mutation points under each area number, and collect the mapped disturbance segment sequence number according to the area number in turn, to generate the rectification interference area demarcation result.

6. The cyclonic sorting based unmanned aerial vehicle water system sediment intelligent sampling method according to claim 1, characterized in that, The cyclone inlet stable section data acquisition step specifically comprises: S211: Based on the rectification interference region delineation result, read the wind speed direction sequence and wind speed amplitude sequence of each time period under the negative pressure path, perform time sequence interception according to each disturbance time period, and combine the rectification plate angle change sequence to perform time reorganization, determine the wind speed direction difference value and wind speed amplitude fluctuation amplitude in the same interval, mark the airflow direction stable section, and generate an airflow stable interval sequence; S212: According to the airflow stable interval sequence, combine the rectification plate opening and closing state signal sequence and the wind speed amplitude change sequence, locate the time period when the rectification plate is not closed, and perform time sequence statistics on the wind speed amplitude value sequence in the section according to the continuous descending section, obtain the continuous time distribution section, and generate a wind speed stable suction section; S213: Based on the wind speed stable suction section, according to the spatial arrangement position coordinate data of the cyclone inlet sensor, perform spatial index conversion on the airflow sensor number corresponding to each stable suction section, locate the duct coordinate section, map the start and end time of each stable suction section and mark it as a cyclone inlet segment, and generate cyclone inlet stable section data.

7. The cyclonic separation based unmanned aerial vehicle stream sediment intelligent sampling method according to claim 1, characterized in that, The sedimentation layer screening alignment interval obtaining step specifically comprises: S311: After collecting the cyclone inlet stable section data, obtain the particle rotation speed sequence corresponding to each time node in the cyclone cavity, calculate the particle critical settling velocity at each time point rotation speed, and analyze the particle settling velocity field at different radial positions to obtain particle settling velocity distribution data; S312: According to the particle settling velocity distribution data, read the guide vane angle setting value and the standard sedimentation particle density interval, cut the speed field at different rotation speeds according to the angular direction according to the deflection force line direction formed by each guide vane angle, establish a sedimentation flow field sub-region under the deflection of the guide vane, calculate the sedimentation path region boundary value formed by each guide vane angle, compare it with the standard sedimentation layer thickness threshold, exclude the path distribution section that does not form a layered structure, and generate a sedimentation path layered interval according to the remaining region; S313: Based on the sedimentation path layered interval, compare the actual measurement value of each screen hole aperture in the screen structure with the standard screen mesh tolerance range setting value, extract the layered path boundary interval that meets the upper and lower limit envelope conditions of the screen hole, and in all matching sections, count the continuous length and number sequence, mark and collect the path boundary that can be directly aligned, establish a number index table, and generate a sedimentation layer screening alignment interval.

8. The cyclone separation based unmanned aerial vehicle water system sediment intelligent sampling method according to claim 7, characterized in that, The screen alignment execution record obtaining step specifically comprises: S411: Based on the sedimentation path layered interval, read the displacement record of the screen cylinder at each time node, compare the coordinate position in the displacement state data with the physical boundary range value of the corresponding section of the target interval, calculate the relative offset amount of the screen edge positioning point and the boundary start and end coordinates, and generate displacement alignment offset amount data; S412: According to the displacement alignment offset data, it is judged whether the current alignment direction of the screen is in the target interval, and it is analyzed whether the coordinate difference value between the bottom and the top of the screen is completely in the boundary. If it is not in the boundary, the direction signal of the slide rail driver is obtained according to the offset direction flag bit until the offset is zero, and the screen boundary alignment determination result is obtained; S413: Based on the screen boundary alignment determination result, the time recorder of the current coordinate position is started in the screen alignment state, the holding time of the screen from the last displacement completion to the current static state is collected, and the slide rail number corresponding to the number and the coordinate number are recorded. The time data and the screen number data are stored in association to generate the screen alignment execution record.

9. The cyclonic separation based unmanned aerial vehicle stream sediment intelligent sampling method according to claim 1, characterized in that, The intelligent sampling record acquisition step of the unmanned aerial vehicle water system sediment is specifically: S511: Based on the screen alignment execution record, the time stamp and screen number information of the screen trigger action are extracted, the opening state flag and state time stamp of the rectifier plate at the corresponding time are obtained in turn, it is judged whether there is a record of the rectifier plate state flag in the same window, if there is, the corresponding screen number is marked in the time period, and the interference state is generated. The rectification cross interference marking record is generated; S512: According to the rectification cross interference marking record, the corresponding screen number in the marked section is extracted, it is detected whether the state after each alignment is completed is paused, the end time when the last state flag of the screen is invalid is recorded, if the rectifier plate state sequence appears completely opened state, the corresponding time stamp is recorded and the screen number is bound, and the screen unlocking time stamp is obtained; S513: Based on the screen unlocking time stamp as a time base point, all action records after the corresponding time point of the corresponding screen number are read in turn, and the rectifier plate state change sequence and the negative pressure path on-off state sequence are extracted. The record items are arranged in order of time in turn to generate the intelligent sampling record of the unmanned aerial vehicle water system sediment.

10. An unmanned aerial vehicle (UAV) water system sediment intelligent sampling system based on cyclone sorting, characterized in that, The system is used to realize the unmanned aerial vehicle water system sediment intelligent sampling method based on cyclone sorting according to any one of claims 1-9, and the system comprises: The wind speed disturbance recognition module is used to execute S1: obtaining the cyclone sorting sampling head re-entrant direction change sequence, disturbance occurrence time period and rectifier plate deflection trajectory, counting the disturbance direction change number and rectifier plate angle mutation point, mapping the position with the rectifier plate response area, and generating the rectification interference area demarcation result; The stable path determination module is used to execute S2: based on the rectification interference area demarcation result, identifying the air suction steady-state segment corresponding to the cyclone inlet, and marking the cyclone inlet position, and generating the cyclone inlet stable section data; The deposition interval positioning module is used to execute S3: based on the cyclone inlet stable section data, collecting the rotation speed sequence in the cyclone cavity, the guide angle setting value and the standard deposition particle density interval mapping relationship, screening the screen interval boundary that can be directly aligned with the screen structure, and generating the deposition layer screening alignment interval; The screen path control module is used to execute S4: according to the deposition layer screening alignment interval, it is judged whether the screen height enters the target interval boundary, if not in the boundary, the alignment operation is executed, and the screen alignment execution record is generated; The screen path control module is used to execute S4: according to the deposition layer screening alignment interval, it is judged whether the screen height enters the target interval boundary, if not in the boundary, the alignment operation is executed, and the screen alignment execution record is generated; The linkage process recording module is configured to perform S5: performing recording based on the screen alignment, identifying the intersection of the current opening state of the rectifier plate and the action trigger time of the screen, recording the rectifier adjustment, the screen action, and the negative pressure path state stage information, and generating the unmanned aerial vehicle water system sediment intelligent sampling record.

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