Fish spawning site recognition regulation and control device and method

Abstract

The invention discloses a fish spawning site recognition regulation and control device and method.The device comprises a gravel base and bionic aquatic plants fixed to the gravel base, the bionic aquatic plants comprise bionic blades, bionic rhizomes and a turnover control device, and the turnover control device drives the bionic rhizomes to rotate to achieve angle turnover of the bionic blades; adsorption control devices are embedded in the gravel bases, and adsorption between the adjacent gravel bases is achieved through magnetic force; after the device is put, a sensor assembly on the device is used for collecting pressure and flow field data in a putting area, roe adhesion indexes are calculated so as to determine the roe adhesion condition on the device in the area, and the gravel base or the bionic aquatic plants are further adjusted so that the flow field in each area can be close to the ideal oviposition environment of target fishes. The system can adapt to most river terrain environments and intelligently recognize the spawning environment, and meanwhile, self-adaptive regulation and control can be carried out according to the change of a flow field, so that spawning proliferation of fishes is effectively promoted.

Description

Technical Field

[0001] The invention relates to the field of water ecological environment protection, and in particular to a device and method for identifying and regulating fish spawning grounds. Background Art

[0002] While water conservancy and hydropower projects play a comprehensive role in flood control, power generation, and shipping, they are also likely to have a certain impact on the ecological environment. The connectivity of aquatic habitats is blocked by dams and gates, causing the decline of migratory fish populations, resulting in the loss of natural habitat conditions for spawning by most fish, affecting the reproduction and development of spawning fish. Some spawning fish need to attach their eggs to the leaves of aquatic plants during the breeding season for hatching and development. However, the water environment with aquatic plants in natural rivers is gradually decreasing. In addition, the decline in water levels has reduced the spawning area of ​​spawning fish to a certain extent, and it is also easy to cause the laid fish eggs to be exposed to the air and die due to lack of oxygen and exposure.

[0003] The quality of the spawning habitat directly affects the stability and sustainable development of fish populations. In order to build a good fish spawning environment, artificial intervention can be used for proliferation and restoration. By placing certain artificial fish nests, artificial fish nests use bionic aquatic plants to simulate the fish ecological environment, set up in specific waters, for fish spawning and reproduction and juvenile (young) fish to live and grow, it is beneficial to improve fish spawning conditions, achieve fish proliferation and habitat restoration. However, most of the existing artificial fish nest technologies are placed in shallow waters with slow flow near the coast and are anchored at a fixed point. They are not adaptable to water levels and terrains, and their scope of application is limited to specific spawning fish within a certain water level range. They are not versatile and adaptable, and cannot be applied to the application needs of multiple fish or water changes. They cannot also realize functions such as intelligent identification of fish spawning grounds and adaptive regulation of surrounding flow fields. Summary of the invention

[0004] Purpose of the invention: The purpose of the present invention is to provide a fish spawning ground identification and control device and method, which can adaptively adjust its own state based on the identified water environment to build a flow field environment suitable for target fish spawning.

[0005] Technical solution: To achieve the above-mentioned purpose, the present invention provides a fish spawning ground identification and control device, which includes a gravel base and bionic aquatic plants fixed on the gravel base. The bionic aquatic plants include bionic blades, bionic rhizomes, and a flip control device. The flip control device drives the bionic rhizomes to rotate to achieve the angle flipping of the bionic blades. The gravel base is embedded with an adsorption control device, which generates magnetic force to achieve adsorption between adjacent gravel bases. The gravel base or the surface of the bionic aquatic plants is provided with a sensor component.

[0006] The bionic water grass is connected to the bionic rhizome through twisted wires, and the bionic water grass is made of nylon fibers, and has a reticular structure on the surface.

[0007] Among them, the flipping control device includes a first control unit and a servo mechanism. When the first control unit receives a flipping signal, the servo mechanism is controlled to drive the bionic rhizome to rotate; the adsorption control device includes a second control unit and an electromagnet. When the second control unit receives an adsorption signal, the electromagnet is controlled to work, so that the electromagnet in the adjacent gravel base generates a repulsive force.

[0008] The gravel base includes one or more gravel combinations, which are divided into a fine gravel base, a medium gravel base, and a coarse gravel base according to the particle size of the gravel.

[0009] Wherein, the sensor component includes a flow rate sensor and a pressure sensor.

[0010] The identification and control method based on the above-mentioned fish spawning ground identification and control device described in the present invention comprises the following steps:

[0011] S1: Assess the spawning suitability of target fish species in the river to be released and identify the most suitable water area;

[0012] S2: Divide the water area into multiple grid units, calculate the spawning suitability of target fish in each grid unit, and determine the grid unit for placing the fish spawning ground identification and control device;

[0013] S3: using the fish spawning ground identification and control device to collect the pressure and flow field data in the grid unit, and calculate the fish egg adhesion index R of the target fish in each grid unit;

[0014] S4: Based on the fish egg adhesion index R in the grid unit and the target fish's preference for the flow field, the fish spawning ground identification and control device is used to control the flow field in the grid unit to form a flow velocity environment that meets the preferences of the target fish.

[0015] Among them, the method of evaluating the spawning suitability of the target fish species to be released into the river channel and dividing the most suitable water area in S1 is as follows: based on multi-source remote sensing data and slope elevation data, the local gradient coefficient of the center line of the river channel and the elevation of the center point of the river channel are calculated and a generalized underwater terrain map is simulated; the measured spectrum and historical measured water temperature data are learned by machine learning algorithms to construct a surface water temperature inversion model for the selected water area; the most suitable water area is divided by comparing the surface water temperature predicted by the surface water temperature inversion model with the water temperature range required for spawning and reproduction of the target fish species.

[0016] Among them, S2 divides the water area into multiple grid units, and the method for calculating the spawning suitability of target fish in each grid unit is as follows: according to the measured water area topography and water level data of the water area, the water area is divided into multiple grid units, and the water temperature and dissolved oxygen data of each grid unit are collected to calculate the spawning suitability score of the target fish in each grid unit. j :

[0017] score j =σ j ×(T j ×R j );

[0018] In the formula, score j represents the suitability score at the jth grid cell, T j represents the temperature suitability of the jth grid cell, R j represents the dissolved oxygen suitability of the jth grid cell, σ j Indicates T j and R j The comprehensive weight factor of

[0019] About T j and R j , the calculation method is:

[0020]

[0021] In the formula, T is the water temperature suitability, T x T is the water temperature at the device placement point; up T is the upper threshold of water temperature suitable for spawning of target fish; down The lower threshold of water temperature suitable for spawning of target fish;

[0022]

[0023] In the formula, R is the suitability of dissolved oxygen, R x is the dissolved oxygen concentration at the device placement point; R up R is the upper threshold of dissolved oxygen concentration suitable for spawning of target fish; down It is the lower threshold of dissolved oxygen concentration suitable for spawning of target fish.

[0024] Among them, the method of determining the fish egg adhesion index of the target fish in each grid unit in S3 is as follows: in each grid unit, firstly, based on the pressure and flow field data collected by each sensor component on the fish spawning ground identification and control device, a single fish egg adhesion index R is calculated. vp :

[0025]

[0026] Where v' is the fluctuation value of the flow field data collected by a single sensor component, p' is the fluctuation value of the pressure data collected by a single sensor component, and the fluctuation value is the instantaneous value collected at each moment minus the time average value based on the time series; x r ,y r is the coordinate of the preset control point, Δx and Δy are the distribution density of grid units; when R vp When it is greater than the set adhesion index threshold, it is determined that fish eggs are adhered to the surface of the device near the sensor component;

[0027] The average of all calculated fish egg adhesion indices in each grid unit is calculated to obtain the fish egg adhesion index R of each grid unit:

[0028]

[0029] Where n represents the number of sensor components in the grid unit.

[0030] Among them, in S4, based on the fish egg adhesion index R in the grid unit and the target fish's preference for the flow field, the method of using the fish spawning ground identification and control device to control the flow field in the grid unit is: using the fish spawning ground identification and control device to control the flow field of the grid unit whose fish egg adhesion index R is greater than the set adhesion index threshold, so as to form a flow velocity environment that meets the preferences of the target fish;

[0031] The control method is: if the current flow rate in the grid unit to be controlled is greater than the preferred flow rate of the target fish, the flip control device is used to drive the bionic root to rotate, and then drive the bionic blade to flip to increase the contact area with the water flow, or the adsorption control device is used to make the adjacent gravel bases adsorb each other to form a multi-layer stacking structure or an arrangement of different densities to reduce the flow rate in the grid unit;

[0032] If the current flow velocity in the grid unit to be regulated is lower than the preferred flow velocity of the target fish, the flipping control device is used to drive the bionic blade to flip to reduce the contact area with the water flow, or the adsorption control device is used to make the nearby gravel bases move away from each other to increase the flow velocity in the grid unit.

[0033] Beneficial effects: The present invention has the following advantages: 1. The present invention obtains the adhesion of fish eggs based on the collected pressure and flow field data, and can adaptively adjust the blade angle of the bionic water grass and the adsorption state of the gravel base to build a spawning environment that is more suitable for the target fish, thereby meeting the spawning needs of various fish in the river; 2. The fish spawning ground identification and control device of the present invention and the method thereof are suitable for rivers, streams, artificial rivers, etc.; 3. The design of the gravel base and bionic water grass simulates the environment of natural water grass and provides a suitable spawning place for fish. At the same time, the bionic blades made of nylon fiber are reticulated to increase the attachment points of fish eggs; 4. The present invention can realize different adjustment forms of gravel base adsorption according to actual needs, such as multi-layer stacking structure, arrangement of different densities, etc., with strong flexibility. BRIEF DESCRIPTION OF THE DRAWINGS

[0034] Figure 1 It is a schematic diagram of the process of the present invention;

[0035] Figure 2 Grid division diagram for a watershed;

[0036] Figure 3 Collect spawning suitability maps for a watershed;

[0037] Figure 4 Illustration of bionic water plants Figure 1 ;

[0038] Figure 5 Illustration of bionic water plants Figure 2 ;

[0039] Figure 6 Schematic diagram of different adjustment modes of adsorption on the gravel base of the present invention. DETAILED DESCRIPTION

[0040] The technical solution of the present invention is described in detail below in conjunction with the embodiments and drawings.

[0041] The fish spawning ground identification and control device described in the present invention includes a gravel base and a bionic water grass fixed on the gravel base. The bionic water grass includes bionic blades, bionic rhizomes, and a flip control device, wherein the blades of the bionic water grass are long and flat, made of nylon fiber, and the surface is reticulated to provide more attachment points for fish eggs. The bionic water grass is connected to the bionic rhizomes by twisted wires. The bionic rhizomes include one or more curved segments, which are driven to rotate by the flip control device, and further realize the angle flipping of the bionic blades. The curved segments can be set to different shapes of curvature according to actual applications, such as C-shape, S-shape or other shapes.

[0042] The flip control device includes a first control unit and a servo mechanism. When the first control unit receives a flip signal, the servo mechanism is controlled to drive the bionic root to rotate, so that the bionic blade can flip at an angle. At the same time, during the rotation process, multiple curved segments can be brought closer to and separated from each other, thereby providing flip characteristics and flexibility at different angles.

[0043] The gravel base is composed of one or more gravels, and can be divided into a fine gravel base, a medium gravel base, and a coarse gravel base according to the particle size of the gravel. The gravel can be an artificial stone, and an adsorption control device is embedded inside. The adsorption control device includes a second control unit and an electromagnet. When the second control unit receives an adsorption signal, it controls the electromagnet to work so that the electromagnets in adjacent gravel bases generate adsorption force, so as to approach each other. At the same time, the electromagnets in adjacent gravel bases can also generate repulsive force to keep adjacent gravel bases away from each other. In this way, different adjustment forms of gravel base adsorption are realized, such as multi-layer stacking structure, arrangement of different densities, etc. These adjustment forms can be designed and adjusted according to actual needs to adapt to different application scenarios.

[0044] The design of the gravel base and bionic water plants simulates the environment of natural water plants and provides a suitable spawning place for fish. The bionic blades made of nylon fiber are reticulated to increase the attachment points of fish eggs and reduce the loss of fish eggs due to water flow or other factors. At the same time, the shape, size and arrangement of the blades can be adjusted according to the differences in the spawning habits of different fish to further simulate different types of water plant environments and attract target fish. The flip control device enables the bionic blades to adjust the angle of the blades according to environmental changes and meet the needs of various fish for spawning environments. The adsorption control device allows the gravel base to form a multi-layer stacking structure or an arrangement of different densities, which helps to create a diverse microenvironment.

[0045] One or more sensor components are evenly distributed on the above-mentioned group of gravel bases and the bionic water plants fixed thereon, including flow rate sensors and pressure sensors, which are used to collect pressure data p and flow field data v near the distribution points of the sensor components. In practical applications, after the waters that can be placed are determined by calculating the suitability of fish spawning, the water body is divided into multiple grid units, and one or more groups of the above-mentioned fish spawning ground identification and control devices are placed in each grid. Through the data collection of the sensor components, the time series of pressure data P and flow field data V near the distribution points of each sensor component in the grid unit are obtained, and based on the time series, the fish egg adhesion index near the distribution point is calculated, and the fish egg adhesion index obtained based on each sensor component in the grid unit is averaged, so as to obtain the fish egg adhesion situation in the grid unit. If the grid unit is determined to be a fish spawning ground, in order to cater to the mating and spawning preferences of the target fish, according to the actual hydrodynamic and water environment characteristics, the gravel base or bionic water plants are adjusted by using the flip control device and the adsorption control device to make the flow field of the grid unit close to the ideal spawning environment of the target fish.

[0046] The specific identification and regulation process includes the following steps:

[0047] 1. Construct a surface water temperature inversion model. Based on multi-source remote sensing data and slope elevation data, calculate the local gradient coefficient of the river centerline and the elevation of the river center point and simulate the underwater terrain generalization map. Use machine learning algorithms to learn the measured spectrum and historical measured water temperature data to construct a surface water temperature inversion model for the selected water area.

[0048] Second, by comparing the surface water temperature predicted by the surface water temperature inversion model with the water temperature range required for spawning and reproduction of target fish, the suitability of the water area is evaluated, and the most suitable water area is further divided, such as the water area with a water temperature of 15-25℃;

[0049] 3. Divide the water area into a plurality of grid units according to the measured water area topography and water level data of the water area, collect water temperature and dissolved oxygen data of each grid unit to calculate the spawning suitability of target fish in each grid unit, and take the top 70% of the grid units with the best spawning suitability of fish as the placement points of the fish spawning ground identification and control device;

[0050] The calculation process is:

[0051]

[0052] In the formula, T is the water temperature suitability, T x —Water temperature at the location where the device is placed; T up —The upper threshold of water temperature suitable for spawning of target fish; T down —The lower threshold of water temperature suitable for spawning of target fish;

[0053]

[0054] In the formula, R is the suitability of dissolved oxygen, R x —Dissolved oxygen concentration at the device placement location; R up —The upper threshold of dissolved oxygen concentration suitable for spawning of target fish; R down —The lower threshold of dissolved oxygen concentration suitable for spawning of target fish;

[0055] Calculate fish spawning suitability for a grid cell:

[0056] score j =σ j ×(T j ×R j );

[0057] In the formula, score j —The suitability score at the jth grid cell, T j —Temperature suitability of the jth grid cell, R j —Dissolved oxygen suitability of the jth grid cell, σ j —Corresponding to T j and R j The comprehensive weight factor.

[0058] Fourth, in each grid unit, the sensor components on each device collect the pressure and flow field near the distribution point, and send them to the back-end signal processing platform. The back-end signal processing platform calculates the adhesion of fish eggs near each distribution point based on the data uploaded by each sensor component;

[0059] The calculation process is:

[0060]

[0061] Where v' is the fluctuation value of the flow field data collected at the distribution point, p' is the fluctuation value of the pressure data collected at the distribution point, and the fluctuation value is the instantaneous value collected at each moment minus the time average value based on the time series; x r ,y r are the coordinates of the preset control points, which were determined through spawning in previous years and preliminary tank experiments, and Δx and Δy are the distribution densities of the grid cells.

[0062] The average of the fish egg adhesion indexes calculated for all distribution points in a single grid unit is calculated to obtain the fish egg adhesion index of the grid unit:

[0063] n represents the number of sensor components in the grid unit. If R is greater than 0.5, it is determined that fish eggs are adhered to the surface of the device in the grid unit.

[0064] 5. Count the fish eggs adhesion on the device surface in each grid unit, and further adjust the gravel base or bionic water plants to make the flow field in each grid unit close to the ideal spawning environment of the target fish.

[0065] The adjustment conditions are: when R>0.5, the flow field is controlled according to the preferences of the target fish, and the flow field control range is 0.33~1.50m / s. For example, the four major carps and the Chinese sturgeon can only spawn when the flow rate is greater than 1m / s.

[0066] The control method is: if the flow rate is greater than the preferred flow rate of the target fish, the flip control device is used to drive the bionic root stem to rotate, and then drive the bionic blade to flip to increase the contact area with the water flow, or add the adsorption adjustment of the gravel base on the basis of the above adjustment, so that adjacent or close gravel bases adsorb each other to speed up the flow field control. If the flow rate is less than the preferred flow rate of the target fish, the flip control device is used to drive the bionic root stem to rotate, and then drive the bionic blade to flip to reduce the contact area with the water flow, or add the repulsion adjustment of the gravel base on the basis of the above adjustment, so that adjacent or close gravel bases are far away from each other.

[0067] Taking a certain river basin A as an example, the working principle of the identification and control method based on the fish spawning ground identification and control device of the present invention is as follows: Figure 1 As shown in the figure, based on multi-source remote sensing data and slope elevation data, the river centerline, local gradient coefficient and river center elevation of Basin A are calculated and the underwater terrain generalization map is simulated. The measured spectrum and historical measured water temperature data are learned using machine learning algorithms to build a surface water temperature inversion model. Secondly, based on the measured water area terrain and water level data and the water temperature data suitable for fish spawning and reproduction, the water body with a water temperature of 15-25℃ in the river is divided into multiple grid cells, such as Figure 2 As shown, the size of each grid unit is 10m*10m, and the fish spawning suitability score of each grid unit is calculated by the water temperature suitability T and dissolved oxygen suitability R. The top 70% points of fish spawning suitability are taken as the device deployment points. Figure 3 Display the grid cells in Basin A that meet the requirements for fish spawning suitability scores. This process is to accurately find the spawning sites for fish and make preliminary preparations for subsequent precise delivery.

[0068] After the placement point in the watershed is determined, the device is placed, and the spawning recognition module monitors the time series data of pressure data P and flow field data V and identifies fish eggs and excludes non-fish eggs adhering to the device surface. vp When it is greater than 0.5, it is determined that this is a fish spawning ground. In order to cater to the fish's mating and spawning preferences, the device enters the adaptive control module according to the actual hydrodynamic and water environment characteristics. Based on the flow field data monitored in real time by the device, such as Figure 4 , 5 As shown in FIG. 1 , the bionic blades in the bionic water grass module are connected by twisted wires and bionic rhizomes, which can realize the angle flipping of the bionic blades and the bending deformation of the bionic water grass rhizomes, and regulate the surrounding flow field by increasing the contact area with the water flow; Figure 6 As shown, the matrix base module controls the mutual adsorption of different sub-domain matrices to form a flow field containing multiple flow states, and also realizes the regulation of the surrounding flow field to create an optimal flow field suitable for fish.

Claims

1. A device for identifying and controlling fish spawning grounds, characterized in that: It includes a gravel base and bionic water plants fixed on the gravel base. The bionic water plants include bionic blades, bionic rhizomes and a flip control device. The flip control device drives the bionic rhizomes to rotate to achieve the flipping of the angle of the bionic blades. The gravel base is embedded with an adsorption control device, which generates magnetic force to achieve adsorption between adjacent gravel bases. The gravel base or the surface of the bionic water plants is provided with a sensor component.

2. The fish spawning ground identification and control device according to claim 1, characterized in that: The bionic water grass is connected to the bionic rhizome through twisted wires; the bionic water grass is made of nylon fibers and has a reticular structure on the surface.

3. The fish spawning ground identification and control device according to claim 1, characterized in that: The flip control device includes a first control unit and a servo mechanism. When the first control unit receives a flip signal, the servo mechanism is controlled to drive the bionic rhizome to rotate; the adsorption control device includes a second control unit and an electromagnet. When the second control unit receives an adsorption signal, the electromagnet is controlled to work so that the electromagnet in the adjacent gravel base generates a repulsive force.

4. The fish spawning ground identification and control device according to claim 1, characterized in that: The gravel base includes one or more gravel combinations, which are divided into a fine gravel base, a medium gravel base, and a coarse gravel base according to the particle size of the gravel.

5. The fish spawning ground identification and control device according to claim 1, characterized in that: The sensor assembly includes a flow rate sensor and a pressure sensor.

6. An identification and control method based on the fish spawning ground identification and control device according to claim 1, characterized in that: The following steps are involved: S1: Assess the spawning suitability of target fish species in the river to be released and identify the most suitable water area; S2: Divide the water area into multiple grid units, calculate the spawning suitability of target fish in each grid unit, and determine the grid unit for placing the fish spawning ground identification and control device; S3: using the fish spawning ground identification and control device to collect the pressure and flow field data in the grid unit, and calculate the fish egg adhesion index R of the target fish in each grid unit; S4: Based on the fish egg adhesion index R in the grid unit and the target fish's preference for the flow field, the fish spawning ground identification and control device is used to control the flow field in the grid unit to form a flow velocity environment that meets the preferences of the target fish.

7. The fish spawning ground identification and control device according to claim 6, characterized in that: The method for evaluating the spawning suitability of the target fish species in the river to be released and demarcating the most suitable water area in S1 is as follows: based on multi-source remote sensing data and slope elevation data, the local gradient coefficient of the center line of the river and the elevation of the center point of the river are calculated and a generalized underwater terrain map is simulated; the measured spectrum and historical measured water temperature data are learned using a machine learning algorithm to construct a surface water temperature inversion model for the selected water area; the most suitable water area is demarcated by comparing the surface water temperature predicted by the surface water temperature inversion model with the water temperature range required for spawning and reproduction of the target fish species.

8. The fish spawning ground identification and control device according to claim 6, characterized in that: In S2, the water area is divided into multiple grid cells. The method for calculating the spawning suitability of target fish in each grid cell is as follows: according to the measured water area topography and water level data of the water area, the water area is divided into multiple grid cells, and the water temperature and dissolved oxygen data of each grid cell are collected to calculate the spawning suitability score of the target fish in each grid cell. j : score j =σ j ×(T j ×R j ); In the formula, score j represents the suitability score at the jth grid cell, T j represents the temperature suitability of the jth grid cell, R j represents the dissolved oxygen suitability of the jth grid cell, σ j Indicates T j and R j The comprehensive weight factor of About T j and R j , the calculation method is: In the formula, T is the water temperature suitability, T x T is the water temperature at the device placement point; up T is the upper threshold of water temperature suitable for spawning of target fish; down The lower threshold of water temperature suitable for spawning of target fish; In the formula, R is the suitability of dissolved oxygen, R x is the dissolved oxygen concentration at the device placement point; R up R is the upper threshold of dissolved oxygen concentration suitable for spawning of target fish; down It is the lower threshold of dissolved oxygen concentration suitable for spawning of target fish.

9. The fish spawning ground identification and control device according to claim 6, characterized in that: The method for calculating the fish egg adhesion index of the target fish in each grid unit in S3 is as follows: in each grid unit, firstly, based on the pressure and flow field data collected by each sensor component on the fish spawning ground identification and control device, a single fish egg adhesion index R is calculated. vp : Where v' is the fluctuation value of the flow field data collected by a single sensor component, p' is the fluctuation value of the pressure data collected by a single sensor component, and the fluctuation value is the instantaneous value collected at each moment minus the time average value based on the time series; x r ,y r is the coordinate of the preset control point, Δx and Δy are the distribution density of grid units; when R vp When it is greater than the set adhesion index threshold, it is determined that fish eggs are adhered to the surface of the device near the sensor component; The average of all calculated fish egg adhesion indices in each grid unit is calculated to obtain the fish egg adhesion index R of each grid unit: Where n represents the number of sensor components in the grid unit.

10. The fish spawning ground identification and control device according to claim 6, characterized in that: In S4, based on the fish egg adhesion index R in the grid unit and the target fish's preference for the flow field, the method of using the fish spawning ground identification and control device to control the flow field in the grid unit is as follows: using the fish spawning ground identification and control device to control the flow field of the grid unit where the fish egg adhesion index R is greater than the set adhesion index threshold, so as to form a flow velocity environment that meets the preferences of the target fish; The control method is: if the current flow rate in the grid unit to be controlled is greater than the preferred flow rate of the target fish, the flip control device is used to drive the bionic root to rotate, and then drive the bionic blade to flip to increase the contact area with the water flow, or the adsorption control device is used to make the adjacent gravel bases adsorb each other to form a multi-layer stacking structure or an arrangement of different densities to reduce the flow rate in the grid unit; If the current flow velocity in the grid unit to be regulated is lower than the preferred flow velocity of the target fish, the flipping control device is used to drive the bionic blade to flip to reduce the contact area with the water flow, or the adsorption control device is used to make the nearby gravel bases move away from each other to increase the flow velocity in the grid unit.

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