Unmanned aerial vehicle water sediment intelligent sampling method and system based on cyclone separation

Abstract

The invention relates to the technical field of intelligent sampling, in particular to an unmanned aerial vehicle water sediment intelligent sampling method and system based on rotational flow sorting, and the method comprises the following steps: collecting disturbance trajectory and rotational flow data, identifying a stable inlet, screening an alignment interval, executing screen mesh alignment, and generating a sampling record. According to the method, stable section calibration is formed by superposing wind speed direction fluctuation and rectifying plate track change, the screening range is locked to an alignment interval in combination with multi-parameter mapping of the rotating speed and the particle density, and the sediment movement state is captured in a layered mode in a deposition layer through a screen; a whole-process sampling sequence is constructed by a collaborative time sequence of rectification action and screen operation, so that real water disturbance characteristics can be dynamically extracted, sediment movement rules can be matched, the sampling trigger response accuracy is improved, and the screening alignment precision under multi-factor coupling is enhanced; the target section is accurately captured under the interlaced interference of the airflow disturbance and the particle settling process, and the particle layered structure is stably kept.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of intelligent sampling, in particular to a method and system for unmanned aerial vehicle water system sediment intelligent sampling based on cyclone sorting. BACKGROUND

[0002] The technical field of intelligent sampling involves a technical system for sampling, collecting and transmitting target media through automated and intelligent equipment, mainly including a sample collection device, an execution control system, a sampling path planning method and sample identification and processing technology, and is widely used in environmental monitoring, hydrological investigation, agricultural detection and resource exploration, etc. The unmanned aerial vehicle water system sediment sampling method refers to a technical method for collecting surface or bottom sediments in water areas such as rivers, lakes and wetlands by using a remotely controlled or pre-programmed aircraft. A multi-rotor unmanned aerial vehicle carrying a mechanical grabber, a suction pump or a negative pressure collection cabin hovers at a specific coordinate point, and the sediments are adsorbed or collected into the vehicle container by starting the grabbing device or suction assembly at regular intervals to achieve point sampling in the target area.

[0003] In the existing water system sediment sampling process, sampling is mainly carried out by fixed-point hovering and a timing grabbing device. The sampling trigger period cannot dynamically identify the disturbance state, and sample collection relies on mechanical action to complete while ignoring the influence of airflow changes. In a variable water body environment, especially in areas with rapid river flow or sudden flow changes, the matching degree between negative pressure suction and sediment suspension state is low, which can easily lead to mixed sampling particles or particle size deviating from the target range, thereby causing a decrease in analysis data accuracy, interfering with the identification of sediment composition and the judgment of distribution trend, and affecting the reliability of subsequent environmental monitoring and sample tracing results. SUMMARY

[0004] To solve the technical problems existing in the prior art, the present application provides a method for unmanned aerial vehicle water system sediment intelligent sampling based on cyclone sorting, comprising the following steps:

[0005] To achieve the above-mentioned purpose, the present application adopts the following technical solution: a method for unmanned aerial vehicle water system sediment intelligent sampling based on cyclone sorting, comprising the following steps:

[0006] S1: Obtain the cyclone sorting sampling head channel direction change sequence, the disturbance occurrence time period and the fairing deflection trajectory, count the disturbance direction change frequency and the fairing angle mutation point, map the position with the fairing response area, and generate a fairing disturbance area demarcation result;

[0007] S2: Based on the fairing disturbance area demarcation result, identify the air suction steady-state segment at the cyclone inlet and mark the cyclone inlet position to generate cyclone inlet stable section data;

[0008] 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 structure that can be directly aligned with the screen interval boundary, and generating a deposition layer screening alignment interval;

[0009] S4: according to the deposition layer screening alignment interval, judging whether the height of the screen is in the target interval boundary, if not in the boundary, executing alignment operation, and generating screen alignment execution record;

[0010] S5: based on the screen alignment execution record, identifying the intersection of the current opening state of the straightening plate and the screen action trigger time, recording the straightening regulation, screen action and negative pressure path state stage information, and generating unmanned aerial vehicle water system sediment intelligent sampling record.

[0011] As a further scheme of the application, the straightening interference area demarcation result includes the direction change frequency distribution, the angle mutation point position and the interference area mapping relationship, the cyclone inlet stable section data includes the airflow direction stable section 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, and the unmanned aerial vehicle water system sediment intelligent sampling record includes the straightening regulation time sequence, the screen action time sequence and the negative pressure path state sequence.

[0012] As a further scheme of the application, the rotation speed sequence is specifically the critical particle settling rate sequence calculated according to the centrifugal settling formula.

[0013] As a further scheme of the application, the screening interval boundary is specifically the qualified range of standard screen aperture tolerance ± 3%.

[0014] As a further scheme of the application, the straightening interference area demarcation result acquisition step is specifically:

[0015] S111: acquiring the standard anemometer direction change sequence data, the disturbance occurrence time period information and the time sequence trajectory of the deflection angle sensor of the cyclone separation sampling head, performing time alignment, counting the continuous direction change point, the change amplitude and the direction change point number, and generating the disturbance direction change frequency;

[0016] S112: according to the disturbance direction change frequency, performing first order slope calculation on the difference sequence of the deflection angle change value of the straightening plate in each disturbance time period, matching the change trend of the deflection angle of the straightening plate corresponding to the time position of the direction change point, extracting all angle change points, and generating angle mutation point distribution data;

[0017] S113: Based on the angle mutation point distribution data, the response area divided by the rectifier plate structure is divided into intervals, the angle mutation point position index is mapped to the number of the corresponding response area, the mutation point count result under each area number is summarized, the mapped disturbance segment sequence number is sequentially collected according to the area number, and the rectification interference area demarcation result is generated.

[0018] As a further scheme of the present application, the cyclone inlet stable section data acquisition step is specifically:

[0019] S211: Based on the rectification interference area demarcation result, the wind speed direction sequence and the wind speed amplitude sequence of each period under the negative pressure path are read, time sequence interception is performed according to each disturbance period, time reorganization is performed in combination with the rectifier plate angle change sequence, the wind speed direction difference value and the wind speed amplitude fluctuation amplitude in the same interval are determined, the airflow direction stable section is marked, and the airflow stable interval sequence is generated;

[0020] S212: According to the airflow stable interval sequence, the rectifier plate opening and closing state signal sequence and the wind speed amplitude change sequence are combined, the time period when the rectifier plate is not closed is located, and the wind speed amplitude value sequence in the section is time series statistical according to the continuous descending section, the continuous time distribution section is obtained, and the wind speed stable suction section is generated;

[0021] S213: Based on the wind speed stable suction section, according to the spatial arrangement position coordinate data of the cyclone inlet sensor, the airflow sensor number corresponding to each stable suction section is calculated, the coordinate section in the duct is located, the start and end time of each stable suction section is mapped and marked as a cyclone inlet segment, and the cyclone inlet stable section data is generated.

[0022] As a further scheme of the present application, the deposition layer screening alignment interval acquisition step is specifically:

[0023] S311: After collecting the cyclone inlet stable section data, the particle rotation speed sequence corresponding to each time node in the cyclone cavity is obtained, the particle critical settling velocity under the rotation speed of each time point is calculated, and the particle settling velocity distribution data is obtained by analyzing the settling velocity field of the particles at different radial positions;

[0024] S312: According to the particle settling velocity distribution data, the guide flow angle setting value and the standard deposition particle density interval are read, the velocity field under different rotation speeds is cut according to the angular direction according to the deflection force line direction formed by each guide flow angle, the deposition flow field sub-area under the guide flow deflection is established, the deposition path area boundary value formed by each guide flow angle is calculated and obtained, compared with the standard deposition layer thickness threshold, the path distribution section which does not form a layered structure is screened out, and the deposition path layered interval is generated according to the remaining area;

[0025] S313: Based on the deposition path layer interval, according to the comparison between the actual measurement value of each screen aperture in the screen structure and the standard screen tolerance range setting value, the layer path boundary interval meeting the upper and lower limit envelope conditions of the screen aperture is extracted, and the continuous length and number sequence in all matching segments are counted, the path boundary that can be directly aligned is labeled and collected, the number index table is established, and the deposition layer screening alignment interval is generated.

[0026] As a further scheme of the present application, the screen alignment execution record acquisition step specifically comprises:

[0027] S411: Based on the deposition path layer interval, the corresponding screen number is obtained, the displacement record of the screen cylinder at each time node is read, the coordinate position in the displacement state data is compared with the physical boundary range value of the corresponding section of the target interval, the relative offset amount is calculated between the screen edge positioning point and the boundary start and end coordinates, and the displacement alignment offset data is generated;

[0028] S412: According to the displacement alignment offset data, it is judged whether the current alignment direction of the screen is inside the target interval, and it is analyzed whether the coordinate difference value of the bottom and top of the screen is completely inside the boundary, if not, the slide rail driver direction signal is obtained according to the offset amount direction flag, until the offset amount is zero, and the screen boundary alignment determination result is obtained;

[0029] S413: Based on the screen boundary alignment determination result, the time recorder of the current coordinate position is started under 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 and coordinate number corresponding to the number are recorded, the time data and screen number data are associated and stored, and the screen alignment execution record is generated.

[0030] As a further scheme of the present application, the unmanned aerial vehicle water system sediment intelligent sampling record acquisition step specifically comprises:

[0031] S511: Based on the screen alignment execution record, the timestamp of the screen trigger action and the screen number information are extracted, the opening state flag and state timestamp 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 being adjusted, if there is, the corresponding screen number in the time period is marked as being in the interference state, and the rectifier intersection interference marking record is generated;

[0032] S512: According to the rectifier intersection 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 completely open state appears in the rectifier plate state sequence, the corresponding timestamp is recorded and the screen number is bound, and the screen unlocking timestamp is obtained;

[0033] S513: Based on the screen unlocking timestamp as a time base point, all action records after the corresponding time point under the corresponding screen number are read in sequence, and the rectifier plate state change sequence and the negative pressure path on-off state sequence are extracted, the record items are arranged in time sequence in sequence, and the unmanned aerial vehicle water system sediment intelligent sampling record is generated.

[0034] The unmanned aerial vehicle water system sediment intelligent sampling system based on cyclone sorting comprises:

[0035] The wind speed disturbance identification module is used for executing S1: obtaining the cyclone sorting sampling head duct direction change sequence, disturbance occurrence time period and rectifier plate deflection trajectory, counting the disturbance direction change times and rectifier plate angle mutation points, performing position mapping with the rectifier plate response area, and generating the rectifier interference area demarcation result.

[0036] The stable path determination module is used for executing S2: based on the rectifier interference area demarcation result, identifying the air suction steady-state segment corresponding to the cyclone inlet, and labeling the cyclone inlet position, and generating the cyclone inlet stable section data.

[0037] The deposition interval positioning module is used for executing 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.

[0038] The screen path control module is used for executing S4: according to the deposition layer screening alignment interval, judging whether the screen height enters the target interval boundary, if not in the boundary, executing alignment operation, and generating screen alignment execution record.

[0039] The linkage process record module is used for executing S5: based on the screen alignment execution record, identifying the intersection of the current opening state of the rectifier plate and the screen action trigger time, recording the rectifier adjustment, screen action and negative pressure path state stage information, and generating the unmanned aerial vehicle water system sediment intelligent sampling record.

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

[0041] In the present application, the stable section calibration is formed by superimposing the fluctuation of the wind speed direction and the change of the rectifier plate trajectory, the screening range is locked to the alignment interval by combining the multi-parameter mapping of the rotation speed and the particle density, the motion state of the sediment in the deposition layer is captured by the screen in layers, and the full-process sampling sequence is constructed by the coordination of the rectification action and the operation of the screen, so that the real water body disturbance characteristics can be dynamically extracted, the sediment motion law can be matched, the sampling trigger response accuracy can be improved, the screening alignment accuracy under the coupling of multiple factors can be strengthened, and the target section can be accurately captured under the interwoven interference of the air flow disturbance and the particle sedimentation process, the particle layered structure is stably maintained, and the target of the sampling process stage behavior is recorded synchronously. BRIEF DESCRIPTION OF DRAWINGS

[0042] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings needed in the embodiment description will be briefly introduced as follows. Obviously, the drawings in the following description are only some embodiments of the present application, and other drawings can be obtained by those skilled in the art without creative labor.

[0043] Figure 1 The step flowchart of the present application is shown in the figure.

[0044] Figure 2 The acquisition flowchart of the rectification interference area delimitation result of the present application is shown in the figure.

[0045] Figure 3 The acquisition flowchart of the cyclone inlet stable section data of the present application is shown in the figure.

[0046] Figure 4 The acquisition flowchart of the deposition layer screening alignment interval of the present application is shown in the figure.

[0047] Figure 5 The acquisition flowchart of the screen alignment execution record of the present application is shown in the figure.

[0048] Figure 6 The acquisition flowchart of the unmanned aerial vehicle water system sediment intelligent sampling record of the present application is shown in the figure. DETAILED DESCRIPTION

[0049] The technical solutions in the present application will be described below with reference to the drawings.

[0050] In the embodiments of the present application, the words such as "example", "for example" are used to represent as an example, illustration or explanation. Any embodiment or design scheme described as "example" in the present application should not be interpreted as more preferred or more advantageous than other embodiments or design schemes. Rather, the word "example" is intended to present the concept in a specific way. In addition, in the embodiments of the present application, the meaning expressed by "and / or" can be both, or can be one of the two.

[0051] In the embodiments of the present application, "image" and "picture" can be used interchangeably, and it should be pointed out that their meanings are consistent when their differences are not emphasized.

[0052] In the embodiments of the present application, sometimes the subscript such as W1 can be written in the form of non-subscript such as W1, and their meanings are consistent when their differences are not emphasized.

[0053] In order to make the technical problems, technical solutions and advantages to be solved by the present application more clear, the following will be described in detail in combination with the drawings and specific embodiments.

[0054] Please refer to Figure 1 The embodiments of the present application provide an unmanned aerial vehicle water system sediment intelligent sampling method based on cyclone sorting, comprising the following steps:

[0055] S1: Obtain the direction change sequence of the cyclone sorting sampling head, the disturbance occurrence time period and the deflection angle sensor trajectory of the fairing, calculate the disturbance direction change frequency and the corresponding fairing angle mutation point distribution, and perform position mapping with the fairing response area to generate a fairing interference area demarcation result;

[0056] S2: Based on the fairing interference area demarcation result, the stable section of the airflow direction in the negative pressure path and the disturbance decay time period are counted, the continuous time distribution of the fairing non-closed period and the wind speed amplitude reduction area is combined, the air suction steady state segment at the cyclone inlet is identified, and the cyclone inlet position is labeled, and the cyclone inlet stable section data is generated;

[0057] S3: Based on the cyclone inlet stable section data, the rotation speed sequence in the cyclone cavity (the critical settling rate of particles calculated according to the centrifugal settling formula of ISO 13318-2), the guide angle setting value and the standard sediment particle density interval mapping relationship are collected, the sediment path is layered according to the fluid deflection area formed by the rotation speed and the guide angle, the screen interval boundary that the screen structure can directly align (the qualified range of standard screen aperture tolerance ± 3%) is screened, and the deposition layer screening alignment interval is generated;

[0058] S4: According to the deposition layer screening alignment interval, the displacement state data and the alignment direction state of the current screen cylinder along the slide rail are obtained, it is judged whether the height of the screen enters the target interval boundary, if not in the boundary, the slide rail is driven to execute displacement and the alignment position holding time after alignment is labeled, and the screen alignment execution record is generated;

[0059] S5: Based on the screen alignment, execute the record, identify the intersection of the current opening state of the rectifier plate and the action trigger time of the screen, and mark the screen action pause when the rectifier is in the interference adjustment state. Record the screen unlocking trigger time when the rectifier plate resumes opening. Record the rectifier adjustment, screen action, and negative pressure path state information in time sequence to generate the unmanned aerial vehicle water system sediment intelligent sampling record.

[0060] The rectification interference area demarcation result includes the direction change frequency distribution, the angle mutation point position, and the interference area mapping relationship. The cyclone inlet stable section data includes the airflow direction stable section information, the disturbance decay time, and the air intake steady-state segment position. The sediment layer screening alignment interval includes the rotation speed interval, the guide flow angle interval, and the qualified screening boundary. The screen alignment execution record includes the screen height position, the alignment direction state, and the alignment retention time. The unmanned aerial vehicle water system sediment intelligent sampling record includes the rectifier adjustment time sequence, the screen action time sequence, and the negative pressure path state sequence.

[0061] Please refer to Figure 2 , the specific steps of S1 are:

[0062] S111: Obtain the standard anemometer direction change sequence data, disturbance occurrence time period information, and time sequence trajectory of the rectifier plate deflection angle sensor set in the cyclone sorting sampling head duct. Align the time, count the continuous direction change points, change amplitude, and direction change point number, and generate the disturbance direction change frequency;

[0063] To obtain the standard anemometer direction change sequence data, disturbance occurrence time period information, and time sequence trajectory of the rectifier plate deflection angle sensor set in the cyclone sorting sampling head duct, first extract the wind speed direction values collected by each group of anemometers arranged at different positions in the duct cross section. The wind speed direction is recorded in the form of angle. The sampling frequency is set to 10 Hz. The disturbance time period information can be identified by observing the wind speed direction mutation amplitude greater than the preset disturbance identification threshold. The disturbance identification threshold is set to a direction change amplitude of more than 20° within 3 seconds. That is, when there is a data segment with a cumulative direction change amplitude of more than 20° in 30 consecutive sampling points, it is considered as a disturbance segment. After traversing the entire anemometer data sequence under this condition, all disturbance segment start and end times 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 of data will be used as a subsequent reference. For the deflection angle sensor trajectory, extract the angle value changes in the same time range. The sampling frequency is set to 10 Hz. Perform time alignment operation on all disturbance segments, that is, intercept the corresponding time interval of wind speed direction data and deflection angle data. In the identified disturbance segment, perform difference processing according to the direction change value in each second. The difference formula is 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 iThe rectifying plate angle value at the i-th sampling time is represented, and then the slope change in the continuous Δα sequence is calculated. If the slope increases suddenly between two consecutive points, that is, the difference between the Δα values in the two time periods exceeds the slope change threshold, it is identified as an angle mutation point. The slope increase threshold is set to 5° / s. The setting basis is that the natural response amplitude of the rectifying plate under steady-state airflow disturbance is usually not more than 3° per second. In the disturbance section where the anemometer direction changes by more than 20°, the maximum deflection response rate of the rectifying plate is usually 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 as an abnormal fluctuation of non-inertial response driven by wind direction disturbance. This value has a slight upward trend with the increase of the stiffness of the rectifying plate material and the shortening of the sensor sampling interval. When the sampling frequency is increased to 20Hz, the threshold can be increased to 6.2° / s. In 10Hz, 5° / s is used as the upper limit of the steady-state identification. For example, if the Δα sequence is [1, 2, 8, 1], the third point is a mutation point. Map the index of the mutation point to the relative time position in the disturbance section, and match it with the direction change point position obtained in the previous step. If the time of a certain mutation point and the direction change point differ by less than 0.5 seconds, it is considered to be related, forming the rectifying plate mutation response relationship driven by the direction disturbance. Traverse all the disturbance sections and count the angle change point positions that meet the mutation judgment standard in each section. Record the index of the mutation point according to the time position, such as the mutation points in the first disturbance section appearing at 1.6 seconds and 2.9 seconds after the start of the disturbance, corresponding to the 16th and 29th sampling points. Finally, the angle mutation point distribution data is generated.

[0066] S113: Based on the angle mutation point distribution data, the response region interval divided by the rectifying plate structure is divided into intervals, the index of the angle mutation point position is mapped to the number of the corresponding response region, and the count result of the mutation point under each region number is summarized. The number of disturbance sections mapped is collected according to the region number, and the rectification interference region demarcation result is generated.

[0067] Based on the angle mutation point distribution data, the response region interval value set by the rectifying plate structure division is called. The rectifying plate is divided into a number of numbered regions on the duct cross section, each region is 0.1m long, and the whole is divided into 10 regions, numbered from 1 to 10. According to the mapping relationship between the measurement point space position of the rectifying plate deflection angle sensor and the numbered region, for example, sensor A is installed at 0.15m position, which corresponds to numbered region 2. When the mutation point occurs at this position, it is counted into the statistical number of numbered region 2. The spatial coordinate of the index of the mutation point position identified in all disturbance sections is calculated, using the conversion formula X i =L×(i / N), where L is the total length of the rectifying plate, N is the total number of sampling points, and i is the index of the mutation point. For example, a certain mutation point is at the 30th sampling point, L=1m, N=100, then X i= 0.3m, corresponding to the 4th region; map all the mutation point coordinates to the corresponding response region numbers in sequence, and record the number of mutation points contained in each numbered region, then statistically collect them according to the region numbers from 1 to 10, and finally form the mutation point number matrix of each region of the rectifier plate under all disturbance sections to obtain the rectifier interference region demarcation result.

[0068] Please refer to Figure 3 , the specific steps of S2 are:

[0069] S211: Based on the rectifier interference region demarcation result, read the wind speed direction sequence and wind speed amplitude sequence of each period under the negative pressure path, perform time sequence interception according to each disturbance period, and combine the rectifier 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 the airflow stable interval sequence.

[0070] Based on the rectifier interference region demarcation result, call the wind speed direction sequence and wind speed amplitude sequence of each period under the negative pressure path, and perform time sequence interception according to each disturbance period. First, extract the start and end time of each rectifier interference region corresponding time period, and extract the wind speed direction data θ(t) and wind speed amplitude data V(t) in the same time interval from the anemometer record data in the negative pressure channel, where θ(t) is expressed in °, and V(t) is recorded in m / s. The sampling frequency is set to 20Hz, and the rectifier plate angle change sequence α(t) is extracted synchronously. For θ(t) in each time period, perform difference processing, that is, Δθ i = θ i - θ i-1 , if the change value of Δθ in the continuous 5 sampling points is within ±3°, it is determined that the section is directionally stable, for example, Δθ = [2.1, 1.7, 2.5, 0.9, 1.2] in t = 4s to t = 4.25s, which meets the stability criterion. At the same time, calculate the amplitude difference ΔV = max(V t )-min(V t ) of V(t) in the same interval, if ΔV is less than 0.15m / s, it is determined as a wind speed stable section, for example, V = [1.92, 2.01, 1.97, 2.00, 1.96], the amplitude is 0.09m / s, which meets the wind speed stability requirement. Extend 0.5 seconds after the disturbance section, if the extended section V(t) continuously decreases, use the difference ΔV i = V i -V i-1 , if the continuous ΔV i is negative and has no reverse growth point, it is determined as a disturbance decay section. Finally, combine the directionally stable and amplitude stable markers to integrate the time period as the wind speed stable interval sequence, and obtain the airflow stable interval sequence.

[0071] S212: According to the airflow stability interval sequence, combined with the rectifier plate opening and closing state signal sequence and the wind speed amplitude change sequence, the time period when the rectifier plate is not closed is located, and the wind speed amplitude value sequence in the section is sequentially statistically analyzed according to the continuous descending section to obtain the continuous time distribution section, and the wind speed stable suction section is generated;

[0072] According to the airflow stability interval sequence, the rectifier plate opening and closing state signal sequence and the wind speed amplitude value change sequence are called. First, the corresponding time sequence α s (t) is extracted from the rectifier plate control signal, where the state 1 represents closing and the state 0 represents not closing. The α s (t) in the entire airflow stability interval is screened, and the time period when α s (t) = 0 is extracted as the rectifier plate not closed section, for example, the rectifier plate is in a continuous not closed state between t = 6.2s and t = 8.7s; in this not closed section, the wind speed amplitude V(t) is statistically analyzed by sliding window, the window length is set to 1 second, the sampling frequency is 20Hz, the amplitude ΔV = max(V t )-min(V t ) in each window is calculated, and it is judged whether the mean difference ΔV - between two consecutive windows is continuously decreasing. If ΔV - changes more than 0.25m / s between two consecutive windows and the decreasing duration is more than 1.2s, it is determined as an amplitude reduction section, for example, if the window mean value of V(t) decreases from 2.5m / s to 2.2m / s in the interval t = 7.0s to t = 8.4s, then ΔV - = 0.3m / s, which meets the judgment condition; then the marked amplitude reduction time period is intersected with the time period in the airflow stability interval sequence to extract the intersection time range to form a continuous suction period, which is numbered according to the suction continuity to obtain the wind speed stable suction section.

[0073] S213: Based on the wind speed stable suction section, according to the spatial arrangement position coordinate data of the rotational flow inlet sensor, the spatial index conversion of the airflow sensor number corresponding to each stable suction section is calculated, the coordinate section in the duct is located, the start and end time of each stable suction section is mapped and marked as a rotational flow inlet segment, and the rotational flow inlet stable section data is generated;

[0074] Based on the wind speed stable suction section, the spatial arrangement position coordinate data X i and Y iThe spatial position alignment is performed. First, the spatial coordinate positions corresponding to each number are extracted from the sensor layout table arranged at the cyclone inlet, such as sensor number S1 corresponding to X1=0.25 m, Y1=0.40 m, and a spatial position mapping table is established in sequence. The coordinate index matching of the sensor numbers involved in each wind speed stable suction section is performed, and the position area of the cyclone is located, for example, if S1, S2 and S3 are in the suction section, the corresponding inlet is in the interval of 0.2 m to 0.5 m; then the time range of each suction section is registered, for example, the first section starts at t=10.0 s and ends at t=12.8 s, and the corresponding inlet coordinate interval of the section is bound, the space-time pairing is completed, the pairing results of each section are arranged in sequence according to the number sequence, and a stable section number table is established, and finally a stable section set after the alignment of all suction sections and spatial inlet points is formed, and the cyclone inlet stable section data is generated.

[0075] Please refer to Figure 4 , the specific steps of S3 are as follows:

[0076] S311: After collecting the cyclone inlet stable section data, the particle rotation speed sequence corresponding to each time node in the cyclone cavity is obtained, the particle critical settling velocity under the rotation speed of each time point is calculated, and the particle settling velocity distribution data is obtained by analyzing the settling velocity field of the particle at different radial positions;

[0077] After collecting the cyclone inlet stable section data, the particle rotation speed sequence V p (t) corresponding to the number of each inlet section is extracted, the time interval is 10.0 seconds to 14.0 seconds, the sampling interval is 0.02 seconds, the particle rotation speed is monitored in real time by the speed sensor arranged in the radial direction of the rotation cavity, for example, in the section i=1, the particle rotation speed is 2.7 m / s in the section i=2, and 3.5 m / s in the section i=3, and the particle diameter dp i is obtained by the optical diameter measurement module, and the measured values are 38 μm, 45 μm and 40 μm, which are converted into meters and are 3.8×10 -5 m, 4.5×10 -5 m and 4.0×10 -5 m respectively, the medium viscosity η is determined at 25°C and is set to 0.0012 Pa·s, the particle density is measured to be 2650 kg / m 3 , the medium density is 1025 kg / m 3 , and the density difference Δρ p =1625 kg / m 3 . Based on the above values, the settling velocity is calculated according to the following formula:

[0078]

[0079] Take section i = 1 as an example, substitute the data:

[0080]

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

[0082]

[0083] Record the results of each section as follows:

[0084] Table 1 Particle settling velocity calculation table

[0085]

[0086]

[0087] As shown in Table 1, combined with particle size and rotation speed, the settling velocity of particles in each section under the centrifugal sedimentation environment is obtained, which provides a speed reference for subsequent path thickness calculation, and finally the particle settling velocity distribution data is obtained.

[0088] S312: According to the particle settling velocity distribution data, read the guide angle setting value and the standard deposition particle density interval, cut the velocity field under different rotation speeds according to the angle direction formed by the deflection force line direction, establish the deposition flow field sub-region under the guide deflection, use the formula:

[0089]

[0090] Calculate the boundary value of the deposition path region formed by each guide angle, compare it with the standard deposition layer thickness threshold, filter out the path distribution sections that do not form a layered structure, and generate deposition path layered intervals according to the remaining region, wherein ΔZ i represents the deposition path thickness of the i-th section, represents the particle rotation speed [L·T -1 ], L i represents the length of the path in the cyclone region [L], represents the settling velocity of the particle in the direction of gravity [L·T -1 ], which is calculated by the particle density, medium density and particle size according to the formula in ISO13318-2;

[0091] According to the particle settling velocity distribution data, call the guide angle setting value θ a and the particle density interval ρ st , the angle value setting range is 20° to 55°, record the path deflection section under the action of different angles at 5° intervals, and measure the length L i, respectively 0.18m, 0.22m, 0.16m. The deposition path boundary value is calculated according to the formula, as follows:

[0092]

[0093] Table 2 Deposition path boundary calculation table

[0094]

[0095]

[0096] As shown in Table 2, the path boundary value is much larger than the standard threshold of the deposition structure size, so it needs to be screened and processed subsequently to generate the deposition path layered interval.

[0097] The deposition path area boundary value refers to the maximum extension length of the deposition area formed by the particles moving along the flow direction under the combined action of rotation driving and gravity settling in the cyclone chamber, which reflects the farthest spatial position that the particles can finally deposit under the action of given rotation speed, settling speed and structure path length. Its physical meaning is to describe the upper limit of the path that the particles migrate to the stable position in the flow field before the stable position is reached, which is the core index for delimiting the particle layered deposition interface, matching the screen structure size and controlling the separation accuracy. The boundary value is directly controlled by the tangential velocity of the particles, the settling duration and the flow guide channel geometry, so it is often used in engineering applications to judge whether the particles in a section can complete effective deposition within the structure allowed range, and to provide spatial parameter basis for subsequent screen device structure arrangement.

[0098] Formula The operation logic of the formula is based on the spatial displacement behavior of the particles in the cyclone chamber under the action of the centrifugal field. The structure relationship in the expression can be decomposed into the physical meaning combination of "velocity x time", in which represents the settling time of the particles in the gravity direction from the inlet to the center of the flow guide surface, that is, the time that the particles take to move from the inlet to the center of the flow guide surface under the action of the gravity in the path length L i Under the condition of fixed L , the smaller the settling speed is, the longer the residence time of the particles in the section is, and the extension of the residence time will cause the particles to be driven to displace more in the rotation direction. The rotation speed of the particles i is in positive proportion to the displacement length, so the multiplication form is used to couple the operation of the transverse rotation speed and the longitudinal settling time, and the deposition path thickness ΔZ

[0099] S313: Based on the deposition path layer interval, compare the actual measured value of each screen aperture in the screen structure with the standard screen tolerance range setting value, extract the layering path boundary interval that meets the upper and lower limit envelope conditions of the screen aperture, and count the continuous length and number sequence in all matching segments. The path boundary that can be directly aligned is labeled and collected, the numbered index table is established, and the deposition layer screening alignment interval is generated;

[0100] Based on the deposition path layer interval, call the screen aperture specification A s = 0.6m, and its qualified range is A s ±3% = [0.582, 0.618]m, the path boundary ΔZ i is screened and judged, and it is found that the thickness of three path boundaries exceeds the maximum screen tolerance range (344.89m, 262.85m and 296.31m respectively). Therefore, under the current guide angle setting and rotation speed combination, all path thicknesses exceed the screen tolerance limit, and there is no matching section that can be directly screened. This case needs to be adjusted by combining the subsequent speed reduction or diameter reduction control strategy. The current round cannot screen out the matching section, so the numbered archive is empty, and the deposition layer screening alignment interval is an empty set. The result shows that under the current particle density, particle size and guide configuration combination, the formed deposition thickness is too thick, which is not suitable for the current screen, and the rotation speed or fluid shear mechanism needs to be adjusted to reconfigure the path design.

[0101] Please refer to Figure 5 , the specific steps of S4 are:

[0102] S411: Based on the deposition path layer interval, 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 amount of 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 deposition path layer interval, obtain the unique number identification of the screen cylinder at the start time of the operation, and bind it one by one with the annotated deposition path number. Call the slide rail coordinate value recorded by the displacement sensor in the track control unit, read the absolute displacement value and displacement direction flag at each time point, the reading frequency is 50Hz, and the positioning accuracy is set to 0.01m. Compare the coordinate value under each screen number with its corresponding deposition path interval boundary coordinate, and the boundary coordinate is represented by the upper limit Z max and the lower limit Z min , the value range is set by the screening interval formed in the last main step, for example, the boundary of screen number A is Z max = 1.80m, and Z min= 1.42 m, the current screen rail coordinate value is Z s = 1.38 m, the calculated offset is ΔZ = Z min -Z s = 0.04 m, the difference indicates that the screen has not yet entered the interval and needs to continue to move. The offset direction is determined by the positive or negative sign of the current slide rail speed. If v s > 0, it offsets upwards, otherwise it offsets downwards. 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 range are screened out. The screen coordinate value and boundary difference value sequence form an array. Finally, the difference set of the screen cylinder and the target boundary at each time is calculated to obtain the displacement alignment offset data.

[0104] S412: According to the displacement alignment offset data, it is judged whether the current alignment direction of the screen is within the target interval. It is analyzed whether the coordinate difference of the bottom and top of the screen is completely within the boundary. If it is not within the boundary, the slide rail driver direction signal is obtained according to the offset direction flag until the offset is zero. The screen boundary alignment determination result is obtained.

[0105] According to the displacement alignment offset data, the numerical sign of the difference value is first extracted, which is used to judge whether the current moving direction of the screen is consistent with the interval approximation direction. The judgment basis is set as the bottom coordinate Z b of the screen and the top coordinate Z t , that is, Z b = Z s , Z t = Z s + H s , where H s = 0.38 m is the height of the screen structure. The interval boundary is set as Z min = 1.42 m and Z max = 1.80 m. The judgment condition is Z b ≥ Z min and Z t ≤ Z max . If it is not, the ΔZ value in the previous sub-step is called and the direction flag is read. If the flag is negative, the downward moving instruction is started, otherwise the upward moving instruction is started. The increment amplitude of the driver is set as 0.005 m / step to gradually adjust the position of the screen. After each movement, Z b and Z t are reacquired and the judgment is repeated. The iteration process is executed at most 200 times, or until the judgment condition is met. For example, the initial Z s = 1.38 m, then Z t = 1.76 m. This range overlaps with the interval boundary but does not completely contain it, so it needs to continue to move upwards. When Z s = 1.42 m, the condition is met and the iteration is terminated. The screen boundary alignment determination result is obtained.

[0106] S413: based on the screen boundary alignment determination result, start the time recorder for the current coordinate position in the screen alignment state, collect the holding time of the screen from the last displacement completion to the current static state, and record the corresponding numbered slide rail number and coordinate number, associate and store the time data and screen number data, and generate a screen alignment execution record;

[0107] The screen boundary alignment determination result is the judgment result basis. In the screen static state, activate the position recorder, write the current slide rail coordinate Z s , screen number, and record timestamp in the cache area. If the displacement change is less than 0.001m in 20 consecutive records, it is determined that the static state is established, the holding time recording module is started, and the static start time T0 is recorded. The system detects the slide rail state at intervals of 1s. If the slide rail coordinate difference is still less than 0.001m in the subsequent continuous period, the time recording is accumulated. When the slide rail remains in a stable state to T end = T0+15s, the holding time is recorded as 15s, and is written in the track log file together with the current screen number and coordinate data. Finally, the screen number, static start time, holding time, and alignment coordinate are combined to form record data, and a screen alignment execution record is generated.

[0108] Please refer to Figure 6 , the specific steps of S5 are:

[0109] S511: based on the screen alignment execution record, extract the timestamp of the screen trigger action and the screen number information, sequentially obtain the opening state flag and state timestamp of the rectifier plate at the corresponding time, and judge whether there is a record of the rectifier plate state flag in the same window. If there is, mark the corresponding screen number in the time period as an interference state, and generate a rectifier intersection interference marker record;

[0110] Based on the screen alignment execution record, extract the screen number, action start time, and alignment completion time in each record, obtain the state flag sequence of the rectifier plate control module in the same time period, and filter the rectifier state data within 5s before and after each screen action time period. Set the identification window to T s -5s to T e +5s, where T s is the start time of the screen action, and T eFor the end time of the screen action, the state flag value of the rectifier plate in the window is extracted. The state value is a Boolean type, and 1 indicates that the rectification is in the interference adjustment state, and 0 indicates the normal open state. If there is any record with a state value of 1 in the time window, it is determined that the screen action is affected by the rectification, and the identification criterion is set as: screen number A, action start time 13:10:25, action end time 13:10:34, rectifier plate state value 1 in the time period 13:10:29 to 13:10:33, and the determination result is "there is cross interference". The comparison determination logic is whether the value 1 is included in the array [S ti ] or not. If it is included, 1 is written to the flag bit table, otherwise 0 is written. The correspondence between the screen number and the interference determination result is recorded, and the rectification cross interference mark record is obtained.

[0111] S512: According to the rectification cross interference mark record, the corresponding screen number in the marked section is extracted. It is detected whether the state after each alignment is completed is paused or not. The end time when the last state flag of the screen is invalid is recorded. If the completely open state appears in the rectifier plate state sequence, the corresponding time stamp is recorded and bound to the screen number. The screen unlocking time stamp is obtained;

[0112] According to the rectification cross interference mark record, the screen number marked as existing cross interference is extracted. The corresponding action instruction sequence and track motion state data of the screen are obtained in the screen alignment control log. The time period with invalid instruction state is identified as the action pause section. The criterion for judging the pause state is that the screen coordinates do not change and the control signal is "empty instruction" state in the continuous two time records. It is assumed that the screen number B keeps the track position at 1.62 m between 13:20:15 and 13:20:34. The alignment control signal record is empty. It is determined to be in a pause state. The end time of the screen pause is recorded at the end of this time period. Then, all the record times with state flag value 0 in the rectifier plate state change sequence are extracted. The first rectifier state record with a time stamp greater than the pause end time is found, which is set to 13:20:42. The time is recorded as the trigger point of the screen action recovery state. The screen number and the time stamp form a key value group. The screen unlocking time stamp is obtained.

[0113] S513: Based on the screen unlocking time stamp as the time base point, all action records after the corresponding time point of the corresponding screen number are read in sequence, and the rectifier plate state change sequence and the negative pressure path on-off state sequence are extracted. The record items are arranged in chronological order to generate the unmanned aerial vehicle water system sediment intelligent sampling record.

[0114] Call the screen unlocking timestamp as the time base point, read all state change records in the rectifier plate control system, and at the same time extract the screen track control log and negative pressure suction path control log. Set the unlocking time to 13:20:42, then sequentially extract all operation time records after 13:20:42, among which the screen track control records that the screen is displaced at 13:20:44 and sends a locking instruction at 13:20:48, the rectification control changes the state to "adjusting" at 13:20:46, and the negative pressure path control sends a negative pressure on-off signal at 13:20:49, which is set to "path open". Sort the three data in ascending order of time, merge the fields including: timestamp, device module, state type, and action description, record the sequence number after sorting and bind the screen number to write into the database, establish a complete sampling process time trajectory sequence, and generate an unmanned aerial vehicle water system sediment intelligent sampling record.

[0115] The unmanned aerial vehicle water system sediment intelligent sampling system based on cyclone sorting includes:

[0116] The wind speed disturbance identification module is used to perform S1: obtaining the cyclone sorting sampling head duct direction change sequence, disturbance occurrence time period and rectifier plate deflection trajectory, counting the disturbance direction change times and rectifier plate angle mutation points, mapping the positions with the rectifier plate response area, and generating the rectification disturbance area demarcation result;

[0117] The stable path determination module is used to perform S2: based on the rectification disturbance area demarcation result, identifying the air suction steady-state segment at the cyclone inlet, and labeling the cyclone inlet position, and generating the cyclone inlet stable section data;

[0118] The deposition interval positioning module is used to perform 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 structure that can be directly aligned with the screen interval boundary, and generating the deposition layer screening alignment interval;

[0119] The screen path control module is used to perform S4: according to the deposition layer screening alignment interval, judging whether the screen is in the target interval boundary, if not in the boundary, performing alignment operation, and generating screen alignment execution record;

[0120] The linkage process recording module is used to perform S5: based on the screen alignment execution record, identifying the intersection of the current opening state of the rectifier plate and the screen action trigger time, recording the rectifier adjustment, screen action and negative pressure path state stage information, and generating the unmanned aerial vehicle water system sediment intelligent sampling record.

[0121] The above merely illustrates the specific embodiments of the present application, but the protection scope of the present application is not limited thereto, any person skilled in the art can easily think of the changes or replacements within the technical range disclosed by the present application, which should be covered in the protection scope of the present application. Therefore, the protection scope of the present application should be subject to the protection scope of the claims.

Claims

1. A UAV-based intelligent sediment sampling method for aquatic systems based on vortex sorting, characterized in that, Includes the following steps: 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; 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; 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. 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. 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.

2. The intelligent sampling method for unmanned aerial vehicle (UAV) sediments based on vortex sorting according to claim 1, characterized in that, The rectification interference region 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 region. The vortex inlet stable section data 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, the alignment direction status, and the 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.

3. The intelligent sampling method for unmanned aerial vehicle (UAV) sediments based on vortex sorting according to claim 1, characterized in that, The rotational velocity sequence is specifically the sequence of critical settling rates of particles calculated according to the centrifugal settling formula.

4. The intelligent sampling method for unmanned aerial vehicle (UAV) sediments based on vortex sorting according to claim 1, characterized in that, The boundary of the screening interval is specifically the acceptable range of ±3% of the standard screen aperture tolerance.

5. The intelligent sampling method for unmanned aerial vehicle (UAV) sediments based on vortex sorting according to claim 1, characterized in that, The specific steps for obtaining the rectification interference region delineation result are as follows: 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. 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. 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.

6. The intelligent sampling method for unmanned aerial vehicle (UAV) sediments based on vortex sorting according to claim 1, characterized in that, The specific steps for acquiring data in the stable section of the swirl inlet are as follows: 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. 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. 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.

7. The intelligent sampling method for unmanned aerial vehicle (UAV) sediments based on vortex sorting according to claim 1, characterized in that, The specific steps for obtaining the alignment interval for screening the deposition layer are as follows: 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. 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; 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.

8. The intelligent sampling method for unmanned aerial vehicle (UAV) sediments based on vortex sorting according to claim 1, characterized in that, The specific steps for obtaining the screen alignment execution record are as follows: 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. 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. 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.

9. The intelligent sampling method for unmanned aerial vehicle (UAV) sediments based on vortex sorting according to claim 1, characterized in that, The specific steps for obtaining intelligent sampling records of aquatic sediments using unmanned aerial vehicles are as follows: 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. 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. 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.

10. An intelligent sampling system for sediments in aquatic systems based on vortex sorting by unmanned aerial vehicles, characterized in that, The system is used to implement the UAV-based intelligent sediment sampling method for aquatic systems based on vortex sorting as described in any one of claims 1-9, and the system comprises: 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; 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; 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. 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. 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.

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