A mobile benthic organism screen box and method

Abstract

The present application relates to a kind of mobile benthic organism screen box and method, belong to environmental detection technical field, including at least three flushers and rotating motor being sequentially installed in the vertical direction of lower box body, the side end of each flusher is provided with several linear array water outlet, and the both ends of flusher are provided with horizontal motor, and be provided with multiple liquid level sensors. Through multiple liquid level sensors, liquid level in box is monitored in real time.When liquid level exceeds set threshold, automatically close part of sprinkler, prevent sample from water body overflow and cause loss;When liquid level is too low, then start corresponding flusher, both ensure sufficient flushing, and avoid sample damage or loss. Lower box body is provided with flusher that can move horizontally and rotate, cooperate sliding metal pipe with rotating motor, horizontal motor, realize multi-angle, multidirectional three-dimensional flushing, ensure that each surface of benthic organism sample can be effectively cleaned, avoid flushing dead angle.

Description

Technical Field

[0001] This invention relates to the field of environmental monitoring technology, and in particular to a mobile benthic organism screening box and method. Background Technology

[0002] Benthic organism sampling and screening are key technical steps in aquatic environment monitoring and ecological assessment. They are primarily used to obtain biological samples such as aquatic insects, mollusks, and annelids from bottom sediments to analyze the health status of the water body. Current benthic organism screening techniques mainly rely on manual separation using sieves. However, this method has significant limitations in practical applications: benthic organisms are highly susceptible to death or morphological changes after being removed from water, requiring immediate selection at the sampling site and preservation with fixatives (such as formaldehyde or alcohol).

[0003] Existing screening equipment (such as ordinary sieves or fixed sieve boxes) is typically bulky or cumbersome, making it unsuitable for transportation and carrying. Furthermore, the rinsing methods are outdated, reliant on manual labor, and prone to damaging samples. Traditional screening processes rely entirely on manual hand-held water rinsing of the sieves. This method is not only labor-intensive and inefficient, but also difficult to precisely control water pressure. During manual rinsing, excessive water flow can easily cause physical damage to organisms; insufficient flow fails to effectively remove sediment and impurities. Additionally, the physical properties of soil can easily clog the mesh, preventing water from flowing out and causing water accumulation, requiring prolonged waiting times for drainage. Moreover, the lack of standardized rinsing devices leads to significant human error in screening results between different operators, failing to meet the needs of high-throughput, standardized ecological monitoring. This severely impacts the accuracy of subsequent laboratory identification. Summary of the Invention

[0004] This invention overcomes the shortcomings of the prior art and provides a mobile benthic organism screening box and method.

[0005] To achieve the above objectives, the technical solution adopted by the present invention is as follows: The first aspect of this invention provides a mobile benthic organism screening box, comprising: a box body, a connecting ring, and a light-proof and dust-proof cover. The box body is divided into an upper box body and a lower box body, which are detachably connected by a locking mechanism between the upper and lower box bodies. An oscillator and a vibration limiter are installed in the lower box body. An upper sieving screen is installed at the connection between the upper and lower boxes, and at least three flushers are installed in sequence in the vertical direction of the lower box. Each flusher has a sliding metal tube installed on both sides. A rotary motor is installed on the left side of the uppermost and lowermost sliding metal tubes, and a rotary motor is installed on the left end of the middle sliding metal tube. Each flusher has several water outlets arranged in a linear array on its side, and both ends of the flusher are equipped with horizontal motors. Liquid level sensors are installed on the bottom left side of the topmost rotary motor, the bottom left side of the bottommost rotary motor, and the top right side of the middle rotary motor.

[0006] Furthermore, in the mobile benthic organism sieve box, a lower dense sieve is also provided on the bottom of the lower box.

[0007] Furthermore, in the mobile benthic organism screening box, several laser receivers are installed on the left side of the upper box, and several laser emitters are installed on the right side of the upper box.

[0008] Furthermore, in the mobile benthic organism screening box, both the upper and lower boxes are equipped with liquid separation control valves.

[0009] Furthermore, in the mobile benthic organism screening box, a liquid level sensor is also installed on the upper box.

[0010] Furthermore, in the mobile benthic organism screening box, the upper box is equipped with several sprayers arranged in a linear array, and the lower box is also equipped with sprayers on both sides of the top.

[0011] Furthermore, in the mobile benthic organism screening box, the upper box is equipped with an upper water inlet, and the lower box is equipped with a lower water inlet on its side. Both the upper and lower water inlets are provided with threads.

[0012] A second aspect of the present invention provides a control method for a mobile benthic organism sieve box, applied to the mobile benthic organism sieve box, comprising the following steps: Damage tests were conducted on different benthic organism types under different spray parameters, and the probability values ​​of damage to different benthic organism types under different spray parameters were statistically analyzed. A damage probability prediction model is constructed based on the probability values ​​of damage to different benthic organism types under different spraying parameters. The damage probability prediction model is then used to predict the damage probability value of the current benthic organism type under the current spraying parameters. The damage probability value of the current benthic organism type under the current spraying parameters is evaluated to obtain the evaluation result, and the spraying parameters are dynamically optimized based on the evaluation result.

[0013] In the control method of the mobile benthic organism screening box, a damage probability prediction model is constructed based on the probability values ​​of damage to different benthic organism types under different spraying parameters. The damage probability prediction model is then used to predict the damage probability value of the current benthic organism type under the current spraying parameters. Specifically: A damage probability prediction model is constructed based on deep learning, and benthic organism types and spraying parameters are used as nodes to construct a directed descriptive relationship. The nodes are then connected based on the directed descriptive relationship to construct a graph structure. The graph structure is used as the model input of the damage probability prediction model, and the probability value of damage is used as the model output. The damage probability prediction model is trained, and the model parameters of the damage probability prediction model are saved after training. The current benthic organism type and real-time spray parameters are obtained, and the current benthic organism type and real-time spray parameters are input into the damage probability prediction model for prediction. Through prediction, the damage probability value of the current benthic organism type under the current spray parameters is obtained.

[0014] Furthermore, in the mobile benthic organism screening box, the damage probability value of the current benthic organism type under the current spraying parameters is evaluated to obtain the evaluation result, and the spraying parameters are dynamically optimized based on the evaluation result, specifically as follows: Set a damage probability assessment threshold. When the damage probability value of the current benthic organism type under the current spraying parameters is greater than the damage probability assessment threshold, a particle swarm optimization algorithm is introduced, and the number of iterations is set based on the particle swarm optimization algorithm. The spray parameters are reinitialized, and the spray parameters are optimized based on the number of iterations to obtain the spray parameters corresponding to the damage probability value not greater than the damage probability assessment threshold. A spray parameter set is constructed based on the spray parameters corresponding to the damage probability value not greater than the damage probability assessment threshold. Randomly select a candidate spray parameter from the set of spray parameters, estimate the rinsing efficiency of the current mobile benthic organism sieve box based on the candidate spray parameter, and set a rinsing efficiency threshold. When the flushing efficiency of the current mobile benthic organism sieve box is greater than the flushing efficiency threshold, it is used as the final candidate spraying parameter. A final candidate spraying parameter set is generated, and a spraying parameter is selected from the final candidate spraying parameter set as the final spraying parameter. The mobile benthic organism sieve box is sprayed according to the final spraying parameter.

[0015] This invention addresses the shortcomings of the prior art and has the following beneficial effects: This invention utilizes a detachable connection between the upper and lower chambers and two layers of screens with different aperture sizes (a loose upper screen and a dense lower screen), combined with continuous vibration from an oscillator, to achieve automatic grading and efficient filtration of samples based on particle size, significantly improving the separation efficiency of benthic organism samples. Furthermore, a laser emitter and receiver monitor sample blockage in real time, automatically activating the corresponding sprayers to disperse the sample; simultaneously, a liquid level sensor controls the sprayers to reverse-flow and flush the upper screen, effectively preventing screen blockage and water accumulation, ensuring a smooth screening process. Multiple liquid level sensors (located at different heights and positions) monitor the liquid level inside the chamber in real time. When the liquid level exceeds a set threshold, some sprayers are automatically shut off to prevent sample overflow; when the liquid level is too low, the corresponding flushers are activated, ensuring thorough rinsing while avoiding sample damage or loss. Secondly, a horizontally movable and rotatable flushing device is installed in the lower chamber, working in conjunction with a sliding metal tube and rotary and horizontal motors to achieve multi-angle and multi-directional three-dimensional flushing, ensuring that all surfaces of the benthic organism samples are effectively cleaned and avoiding blind spots. Finally, a damage probability prediction model (graph structure) based on deep learning is constructed, and the spray parameters (such as water volume, pressure, and angle) are dynamically optimized using a particle swarm optimization algorithm. While ensuring flushing efficiency, the sample damage probability is controlled below a set threshold, achieving non-destructive or low-damage cleaning of fragile benthic organisms. Through the damage probability prediction model in the control method, optimal spray parameters can be automatically adapted for different benthic organism types (such as mollusks, crustaceans, and polychaetes), making it suitable for processing benthic organism samples in various ecological environments, including marine and freshwater. Furthermore, the start, stop, and intensity of each sprayer and flushing device are automatically adjusted based on the sample volume (determined by laser blocking) and liquid level, avoiding unnecessary water accumulation and waste, and significantly conserving water resources. Attached Figure Description

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

[0017] Figure 1 This is a schematic diagram of the overall component structure of the present invention; Figure 2 This is a schematic diagram of the overall structure of the present invention; Figure 3 This is a schematic diagram of the internal structure of the present invention.

[0018] In the picture: 1. Light-proof and dustproof cover; 2. Connecting ring; 3. Upper chamber; 4. Upper water inlet; 5. Upper and lower chamber locking mechanism; 6. Upper water inlet thread; 7. Lower chamber; 8. Lower water inlet thread; 9. Lower water inlet; 10. Upper and lower chamber locking mechanism; 11. Upper loose screen; 12. Lower dense screen; 13. First laser emitter; 14. First laser receiver; 15. First sprayer; 16. Second laser emitter; 17. Second sprayer; 18. Second laser receiver; 19. Third laser receiver; 20. Fourth liquid level sensor; 21. Third sprayer; 22. Third laser emitter; 23. First liquid distribution control valve; 24. Fifth liquid level sensor; 25. Fourth sprayer; 26. Fifth... Sprinkler, 27, First rotary motor, 28, First liquid level sensor, 29, First horizontal motor, 30, First outlet, 31, Sliding metal tube, 32, Second rotary motor, 33, Second liquid level sensor, 34, Oscillator, 35, Vibration limiter, 36, Third rotary motor, 37, Third liquid level sensor, 38, Second liquid distribution control valve, 39, Second horizontal motor, 40, First sliding metal tube, 41, Sixth sprinkler, 42, First flusher, 43, Second sliding metal tube, 44, Second horizontal motor, 45, Second outlet, 46, Third sliding metal tube, 47, Third horizontal motor, 48, Third outlet, 49, Second flusher, 50, Third flusher. Detailed Implementation

[0019] To better understand the above-mentioned objectives, features, and advantages of the present invention, the present invention will be further described in detail below with reference to the accompanying drawings and specific embodiments. These drawings are simplified schematic diagrams, which only illustrate the basic structure of the present invention in a schematic manner. Therefore, they only show the components related to the present invention. It should be noted that, unless otherwise specified, the embodiments and features in the embodiments of this application can be combined with each other.

[0020] In the description of this application, it should be understood that the terms "center," "longitudinal," "lateral," "upper," "lower," "front," "rear," "left," "right," "vertical," "horizontal," "top," "bottom," "inner," and "outer," etc., indicating orientation or positional relationships based on the orientation or positional relationships shown in the accompanying drawings, are only for the convenience of describing this application and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation, and therefore should not be construed as limiting the scope of protection of this application. Furthermore, the terms "first," "second," etc., are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of indicated technical features. Therefore, features defined with "first," "second," etc., may explicitly or implicitly include one or more of that feature. In the description of this invention, unless otherwise stated, "a plurality of" means two or more.

[0021] In the description of this application, it should be noted that, unless otherwise expressly specified and limited, the terms "installation," "connection," and "linking" should be interpreted broadly. For example, they can refer to fixed connections, detachable connections, or integral connections; they can refer to mechanical connections or electrical connections; they can refer to direct connections or indirect connections through an intermediate medium; and they can refer to the internal communication between two components. Those skilled in the art will understand the specific meaning of the above terms in this application based on the specific circumstances.

[0022] To facilitate understanding of the present invention, a more complete description will be given below with reference to the accompanying drawings. Preferred embodiments of the invention are shown in the drawings. However, the invention can be implemented in many different forms and is not limited to the embodiments described herein. Rather, these embodiments are provided to provide a thorough and complete understanding of the disclosure of the invention.

[0023] like Figures 1 to 3 As shown, the first aspect of the present invention provides a mobile benthic organism screening box, comprising: a box body, a connecting ring, and a light-proof and dust-proof cover. The box body is divided into an upper box body and a lower box body, which are detachably connected by a locking mechanism between the upper and lower box bodies. At least two vibrators are installed in the lower box body. An upper sieving screen is installed at the connection between the upper and lower boxes, and at least three flushers are installed in sequence in the vertical direction of the lower box. Each flusher has a sliding metal tube installed on both sides. A rotary motor is installed on the left side of the uppermost and lowermost sliding metal tubes, and a rotary motor is installed on the left end of the middle sliding metal tube. Each flusher has several water outlets arranged in a linear array on its side, and both ends of the flusher are equipped with horizontal motors. Liquid level sensors are installed on the bottom left side of the topmost rotary motor, the bottom left side of the bottommost rotary motor, and the top right side of the middle rotary motor.

[0024] Furthermore, in the mobile benthic organism sieve box, a lower dense sieve is also provided on the bottom of the lower box.

[0025] Furthermore, in the mobile benthic organism screening box, several laser receivers are installed on the left side of the upper box, and several laser emitters are installed on the right side of the upper box.

[0026] Furthermore, in the mobile benthic organism screening box, both the upper and lower boxes are equipped with liquid separation control valves.

[0027] Furthermore, in the mobile benthic organism screening box, a liquid level sensor is also installed on the upper box.

[0028] Furthermore, in the mobile benthic organism screening box, the upper box is equipped with several sprayers arranged in a linear array, and the lower box is also equipped with sprayers on both sides of the top.

[0029] Furthermore, in the mobile benthic organism screening box, the upper box is equipped with an upper water inlet, and the lower box is equipped with a lower water inlet on its side. Both the upper and lower water inlets are provided with threads.

[0030] It should be noted that after untying the connecting ring 2 and opening the light-proof and dust-proof cover 1, the sample to be screened is placed into the upper chamber 3. The sample falls onto the upper sieve 11 under gravity. The external water source supplies water to the upper chamber 3 and the lower chamber 7 through the upper water inlet thread 6 and the lower water inlet thread 8 via the upper water inlet 6 and the lower water inlet 9. The first liquid separation control valve 23 and the second liquid separation control valve 38 are set to supply water to the sixth sprayer 41, the third sprayer 21, the second sprayer 17, the first sprayer 15, the fourth sprayer 25, the fifth sprayer 26, and the outlet 30 through the sliding metal tube 40.

[0031] When the laser beams from the first laser emitter 13 and the first laser receiver 14 are blocked by the sample, the first sprayer 15 will be activated to flush the sample with water. When the laser beams from the second laser emitter 16 and the second laser receiver 18 are blocked by the sample, the second sprayer 17 will be activated to flush the sample with water. When the laser beams from the third laser emitter 22 and the third laser receiver 19 are blocked by the sample, the sixth sprayer 41 will be activated to flush the sample with water. The amount of flushing water is controlled by the amount of sample to reduce unnecessary water accumulation in the upper chamber 3. When the fourth liquid level sensor 20 detects the liquid level, the fourth sprayer 25 and the fifth sprayer 26 will be opened to re-scrub the upper sieve 11, flushing away the sample attached to the bottom sieve and preventing water accumulation. When the fifth liquid level sensor 24 detects the liquid level, the sixth sprayer 41, the third sprayer 21, the second sprayer 17, and the first sprayer 15 will be closed to prevent the sample from flowing out of the upper chamber 3.

[0032] After the sample passes through the upper loose sieve 11, it flows into the lower chamber 7. Simultaneously, the lower dense sieve 12 at the bottom is lowered by the vibrator 34 and the limiter 35, accelerating the filtration efficiency. When the second liquid level sensor 33 detects the liquid level, it activates the second rotary motor 32 and the third horizontal motor 47, causing the second flusher 49 to move horizontally and rotary along the third sliding metal tube 46, and the water flows through the third outlet 48 to flush the sample. When the third liquid level sensor 37 detects the liquid level, it activates the third rotary motor 36 and the second horizontal motor 44, causing the third flusher 50 to move horizontally and rotary along the second sliding metal tube 43, and the water flows through the second outlet 45 to flush the sample. When the first liquid level sensor 28 detects the liquid level, it activates the rotary motor 27 and the horizontal motor 29, causing the first flusher 42 to move horizontally and rotary along the first sliding metal tube 40, and the water flows through the third outlet 48 to flush the sample. This continues until the sample is completely rinsed.

[0033] In summary, this invention, through the detachable connection of the upper and lower chambers and two layers of screens with different apertures (a loose upper screen and a dense lower screen), combined with the continuous vibration of the oscillator, achieves automatic grading and efficient filtration of samples according to particle size, significantly improving the separation efficiency of benthic organism samples. Furthermore, a laser emitter and receiver monitor sample blockage in real time, automatically activating the corresponding sprayers to disperse the sample; simultaneously, a liquid level sensor controls the sprayers to reverse-flow and flush the upper screen, effectively preventing screen blockage and water accumulation, ensuring a smooth screening process. Multiple liquid level sensors (located at different heights and positions) monitor the liquid level inside the chamber in real time. When the liquid level exceeds a set threshold, some sprayers are automatically shut off to prevent sample overflow; when the liquid level is too low, the corresponding flushers are activated, ensuring thorough rinsing while avoiding sample damage or loss. Secondly, a horizontally movable and rotatable flushing device is installed in the lower chamber, which, together with a sliding metal tube and a rotary and horizontal motor, enables three-dimensional flushing from multiple angles and directions. This ensures that all surfaces of the benthic organism samples are effectively cleaned, avoiding any blind spots. Furthermore, a damage probability prediction model (graph structure) based on deep learning is constructed, and the spray parameters (such as water volume, pressure, and angle) are dynamically optimized using a particle swarm optimization algorithm. While maintaining flushing efficiency, the sample damage probability is controlled below a set threshold, achieving non-destructive or low-damage cleaning of fragile benthic organisms.

[0034] A second aspect of the present invention provides a control method for a mobile benthic organism sieve box, applied to the mobile benthic organism sieve box, comprising the following steps: Damage tests were conducted on different benthic organism types under different spray parameters, and the probability values ​​of damage to different benthic organism types under different spray parameters were statistically analyzed. A damage probability prediction model is constructed based on the probability values ​​of damage to different benthic organism types under different spraying parameters. The damage probability prediction model is then used to predict the damage probability value of the current benthic organism type under the current spraying parameters. The damage probability value of the current benthic organism type under the current spraying parameters is evaluated to obtain the evaluation result, and the spraying parameters are dynamically optimized based on the evaluation result.

[0035] It should be noted that this invention constructs a damage probability prediction model (graph structure) based on deep learning, and dynamically optimizes spray parameters (such as water volume, pressure, angle, etc.) using a particle swarm optimization algorithm. While ensuring rinsing efficiency, the sample damage probability is controlled below a set threshold, achieving non-destructive or low-damage cleaning of fragile benthic organisms. Through the damage probability prediction model in the control method, optimal spray parameters can be automatically adapted for different benthic organism types (such as mollusks, crustaceans, polychaetes, etc.), making it suitable for benthic organism sample processing in various ecological environments such as marine and freshwater.

[0036] In the control method of the mobile benthic organism screening box, a damage probability prediction model is constructed based on the probability values ​​of damage to different benthic organism types under different spraying parameters. The damage probability prediction model is then used to predict the damage probability value of the current benthic organism type under the current spraying parameters. Specifically: A damage probability prediction model is constructed based on deep learning, and benthic organism types and spraying parameters are used as nodes to construct a directed descriptive relationship. The nodes are then connected based on the directed descriptive relationship to construct a graph structure. The graph structure is used as the model input of the damage probability prediction model, and the probability value of damage is used as the model output. The damage probability prediction model is trained, and the model parameters of the damage probability prediction model are saved after training. The current benthic organism type (the target benthic organism type for collection) and real-time spraying parameters are obtained, and the current benthic organism type and real-time spraying parameters are input into the damage probability prediction model for prediction. Through prediction, the damage probability value of the current benthic organism type under the current spraying parameters is obtained.

[0037] It should be noted that different spraying parameters have different damage mechanisms for different benthic organism types. This method can predict the damage probability of different benthic organism types. Deep learning, including convolutional neural networks, recurrent neural networks, and graph neural networks, can be used to construct a damage probability prediction model (graph structure) based on deep learning. Combined with particle swarm optimization, spraying parameters (such as water volume, pressure, and angle) can be dynamically optimized. While ensuring rinsing efficiency, the sample damage probability is controlled below a set threshold, achieving non-destructive or low-damage cleaning of fragile benthic organisms.

[0038] Furthermore, in the mobile benthic organism screening box, the damage probability value of the current benthic organism type under the current spraying parameters is evaluated to obtain the evaluation result, and the spraying parameters are dynamically optimized based on the evaluation result, specifically as follows: Set a damage probability assessment threshold. When the damage probability value of the current benthic organism type under the current spraying parameters is greater than the damage probability assessment threshold, a particle swarm optimization algorithm is introduced, and the number of iterations is set based on the particle swarm optimization algorithm. The spray parameters are reinitialized, and the spray parameters are optimized based on the number of iterations to obtain the spray parameters corresponding to the damage probability value not greater than the damage probability assessment threshold. A spray parameter set is constructed based on the spray parameters corresponding to the damage probability value not greater than the damage probability assessment threshold. Randomly select a candidate spray parameter from the set of spray parameters, estimate the rinsing efficiency of the current mobile benthic organism sieve box based on the candidate spray parameter, and set a rinsing efficiency threshold. When the flushing efficiency of the current mobile benthic organism sieve box is greater than the flushing efficiency threshold, it is used as the final candidate spraying parameter. A final candidate spraying parameter set is generated, and a spraying parameter is selected from the final candidate spraying parameter set as the final spraying parameter. The mobile benthic organism sieve box is sprayed according to the final spraying parameter.

[0039] It should be noted that the spray parameters (such as water volume, pressure, and angle) are dynamically optimized using a particle swarm optimization algorithm. While ensuring rinsing efficiency, the probability of sample damage is controlled below a set threshold, achieving non-destructive or low-damage cleaning of fragile benthic organisms. Specifically, when estimating the rinsing efficiency of the current mobile benthic organism screening box based on the candidate spray parameters, this can be derived from historical experience and recorded reasoning.

[0040] In addition, this method also includes: Miniature industrial cameras are embedded in the side walls of the upper box 3 and the lower box 7, with hydrophobic and anti-fouling coated glass installed in front of the lenses, and multi-angle LED ring lights are installed on the top of the boxes. Embedded motherboards with integrated NPUs (such as the NVIDIA Jetson series) and pre-trained lightweight semantic segmentation models are used for real-time segmentation of complete organisms, organism fragments, and mud and sand particles in images. The initial flushing is initiated, images are acquired using a miniature industrial camera, and a pre-trained lightweight semantic segmentation model is used to segment complete organisms, organism fragments, and mud particles in the images in real time, and the damage index is calculated. If the rate of increase of the damage index within a preset time exceeds the preset rate threshold, it is determined that the water flow impact is too strong. The PID controller will immediately reduce the speed of the water supply pump or adjust the opening of the liquid distribution control valve to reduce the water pressure.

[0041] It should be noted that this method can further reduce physical damage to vulnerable organisms due to water pressure. The damage index is calculated as (fragment area / total biological area) * 100%.

[0042] In addition, this method also includes: Create a high-fidelity 3D model that is completely consistent with the physical device using Unity or Unreal Engine software on a PC or in the cloud, and integrate a CFD solver. Use Unity or Unreal Engine and CFD to build and input the Stokes size distribution of sediment particles, the elastic modulus of organisms, and the turbulence model of water flow. Using the particle swarm optimization algorithm, with coverage uniformity and total energy consumption as dual objective functions, the combination of rotation speed sequence of rotary motor, stroke curve of horizontal motor, and dwell time of sliding metal tube is virtually executed millions of times in a digital twin environment. The particle swarm optimization algorithm is used to generate the optimal joint motion trajectory file, and the offline generated trajectory file is sent to the PLC controller. The physical equipment executes according to the optimal trajectory. At the same time, the sensor data of the actual rinsing is sent back to the digital twin for model calibration.

[0043] It should be noted that this method can further optimize the flushing dead zones. Coverage uniformity is achieved by minimizing the variance of the number of water flow impacts in each area of ​​the tank, and total energy consumption is the sum of water consumption and electricity consumption. The combined motion trajectory file is as follows: the flusher 42 moves from left to right at 20 mm / s, pauses for 0.3 seconds, and then rotates 180° to return. Sensor data includes, for example, the trigger time of the liquid level sensor.

[0044] Furthermore, it should be understood that although this specification describes embodiments, not every embodiment contains only one independent technical solution. This narrative style is merely for clarity. Those skilled in the art should consider the specification as a whole, and the technical solutions in each embodiment can also be appropriately combined to form other embodiments that can be understood by those skilled in the art.

[0045] The embodiments described above are merely specific implementations of this application, used to illustrate the technical solutions of this application, and are not intended to limit it. The protection scope of this application is not limited thereto. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that any person skilled in the art can still modify or easily conceive of changes to the technical solutions described in the foregoing embodiments, or make equivalent substitutions for some of the technical features, within the scope of the technology disclosed in this application; and these modifications, changes, or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of this application. All should be covered within the protection scope of this application. Therefore, the protection scope of this application should be determined by the protection scope of the claims.

Claims

1. A mobile benthic organism screening box, comprising: The enclosure comprises a housing, a connecting ring, and a light-proof and dust-proof cover. The housing is divided into an upper housing and a lower housing, which are detachably connected by a locking mechanism. An oscillator and a vibration limiter are installed in the lower housing. The enclosure is characterized by... An upper sieving screen is installed at the connection between the upper and lower boxes, and at least three flushers are installed in sequence in the vertical direction of the lower box. Each flusher has a sliding metal tube installed on both sides. A rotary motor is installed on the left side of the uppermost and lowermost sliding metal tubes, and a rotary motor is installed on the left end of the middle sliding metal tube. Each flusher has several water outlets arranged in a linear array on its side, and both ends of the flusher are equipped with horizontal motors. Liquid level sensors are installed on the bottom left side of the topmost rotary motor, the bottom left side of the bottommost rotary motor, and the top right side of the middle rotary motor.

2. The mobile benthic organism sieve box according to claim 1, characterized in that, A lower-level dense screen is also installed on the bottom of the lower box.

3. A mobile benthic organism sieve box according to claim 1, characterized in that, Several laser receivers are installed on the left side of the upper housing, and several laser emitters are installed on the right side of the upper housing.

4. A mobile benthic organism sieve box according to claim 1, characterized in that, Both the upper and lower chambers are equipped with liquid separation control valves.

5. A mobile benthic organism sieve box according to claim 1, characterized in that, A liquid level sensor is also installed on the upper box.

6. A mobile benthic organism sieve box according to claim 1, characterized in that, The upper chamber is equipped with several sprayers arranged in a linear array, and the lower chamber is also equipped with sprayers on both sides of the top.

7. A mobile benthic organism sieve box according to claim 1, characterized in that, The upper tank is equipped with an upper water inlet, and the lower tank is equipped with a lower water inlet on its side. Both the upper and lower water inlets are threaded.

8. A control method for a mobile benthic organism sieve box, characterized in that, The mobile benthic organism screening box according to any one of claims 1-7 comprises the following steps: Damage tests were conducted on different benthic organism types under different spray parameters, and the probability values ​​of damage to different benthic organism types under different spray parameters were statistically analyzed. A damage probability prediction model is constructed based on the probability values ​​of damage to different benthic organism types under different spraying parameters. The damage probability prediction model is then used to predict the damage probability value of the current benthic organism type under the current spraying parameters. The damage probability value of the current benthic organism type under the current spraying parameters is evaluated to obtain the evaluation result, and the spraying parameters are dynamically optimized based on the evaluation result.

9. The control method for a mobile benthic organism sieve box according to claim 8, characterized in that, A damage probability prediction model is constructed based on the probability values ​​of damage to different benthic organism types under different spraying parameters. This model is then used to predict the damage probability value of the current benthic organism type under the current spraying parameters. Specifically: A damage probability prediction model is constructed based on deep learning, and benthic organism types and spraying parameters are used as nodes to construct a directed descriptive relationship. The nodes are then connected based on the directed descriptive relationship to construct a graph structure. The graph structure is used as the model input of the damage probability prediction model, and the probability value of damage is used as the model output. The damage probability prediction model is trained, and the model parameters of the damage probability prediction model are saved after training. The current benthic organism type and real-time spray parameters are obtained, and the current benthic organism type and real-time spray parameters are input into the damage probability prediction model for prediction. Through prediction, the damage probability value of the current benthic organism type under the current spray parameters is obtained.

10. The control method for a mobile benthic organism sieve box according to claim 8, characterized in that, The damage probability value of the current benthic organism type under the current spraying parameters is evaluated to obtain the evaluation result, and the spraying parameters are dynamically optimized based on the evaluation result, specifically as follows: Set a damage probability assessment threshold. When the damage probability value of the current benthic organism type under the current spraying parameters is greater than the damage probability assessment threshold, a particle swarm optimization algorithm is introduced, and the number of iterations is set based on the particle swarm optimization algorithm. The spray parameters are reinitialized, and the spray parameters are optimized based on the number of iterations to obtain the spray parameters corresponding to the damage probability value not greater than the damage probability assessment threshold. A spray parameter set is constructed based on the spray parameters corresponding to the damage probability value not greater than the damage probability assessment threshold. Randomly select a candidate spray parameter from the set of spray parameters, estimate the rinsing efficiency of the current mobile benthic organism sieve box based on the candidate spray parameter, and set a rinsing efficiency threshold. When the flushing efficiency of the current mobile benthic organism sieve box is greater than the flushing efficiency threshold, it is used as the final candidate spraying parameter. A final candidate spraying parameter set is generated, and a spraying parameter is selected from the final candidate spraying parameter set as the final spraying parameter. The mobile benthic organism sieve box is sprayed according to the final spraying parameter.

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