A method for preventing the squeezing of fish caught in the inside of a trawl net applied to marine fishery

Abstract

The application discloses a trawl internal fishing catch anti-extrusion square applied to marine fisheries and aims to solve the quality reduction problem caused by fishing catch accumulation in traditional trawl operation. The method comprises the following steps: a distributed sensing array arranged in a trawl net bag is used to monitor physical parameters reflecting the accumulation degree of fishing catch in real time; monitoring data is sent to a central decision and control unit, and whether the activation condition is met is judged according to a preset algorithm; and when the condition is met, a microfluidic adjusting unit is driven. According to the real-time distribution of the pressure in the net bag, the application can calculate and apply differentiated target supporting pressure for different regions of the skeleton network, so that a non-uniform supporting structure matched with the pressure distribution is constructed inside the net bag. The method changes passive stress into active support, can effectively relieve stress concentration, protects the integrity of the fishing catch, and has remarkable practical value.

Description

Technical Field

[0001] This invention relates to the field of marine fishing technology, specifically a method for preventing the crushing of catches inside trawl nets used in marine fisheries. Background Technology

[0002] In commercial fishing operations in marine fisheries, trawls are a widely used and highly efficient fishing tool. However, while traditional trawl designs bring high yields, they also present a long-standing technical challenge that has remained unresolved. During the fishing process, as the catch continuously enters and accumulates in the trawl's innermost section, its immense weight, combined with the dynamic water pressure generated by the trawling process, severely compresses the catch deep within the trawl. This continuous physical pressure often leads to fish deformities, scale loss, internal organ rupture, and even death, significantly reducing the commercial value and economic benefits of the catch. This problem is particularly pronounced for some high-value commercial fish species.

[0003] To alleviate this problem, those skilled in the art have made various attempts. Existing technical solutions typically focus on static structural modifications to the nets. For example, by adjusting the mesh size or shape of the net, it is hoped that some juvenile fish can be filtered out to reduce the total catch within the net. However, this does not change the fundamental nature of the net as a flexible stress-bearing bag; for target fish schools that have reached the catch size, the compression problem still exists when the catch is large. Other solutions attempt to add fixed, rigid fish dividers or escape devices to the net. Their main design purpose is species selectivity, allowing non-target marine life (such as sea turtles) to escape, rather than protecting the quality of the target catch. These rigid structures themselves may cause new abrasion damage to the fish and cannot fundamentally solve the problem of overall, gradual internal pressure accumulation caused by the weight of the catch itself.

[0004] In summary, existing solutions are essentially passive coping strategies. They lack the ability to proactively adjust their structure to counteract pressure based on dynamic changes in catch volume and pressure conditions. The internal space and shape of the trawl net are always passively determined by the catch inside and the external water flow, lacking an effective mechanism to actively expand the space from the inside and relieve stress. Therefore, developing a novel technological solution that can proactively sense the state inside the net and intelligently intervene in internal pressure stress has become a critical technological bottleneck that urgently needs to be addressed to improve trawl fishing efficiency and the economic value of the catch. Summary of the Invention

[0005] To address the shortcomings of existing technologies, this invention provides a method for preventing the crushing of catch inside trawl nets in marine fisheries. The technical problem to be solved is that in existing marine fisheries trawl operations, the continuous accumulation of catch within the net, combined with its own weight and water flow, leads to severe crushing of the catch at the rear end of the net, thereby reducing the quality and economic value of the catch. Existing technologies mostly employ passive or static structural modifications, which cannot actively counteract and alleviate the crushing stress based on the dynamic changes in the catch volume.

[0006] To achieve the above objectives, the present invention is implemented through the following technical solution: a method for preventing crushing of catches inside trawls in marine fisheries. This method deploys an intelligent system that can dynamically change its shape inside the trawl net bag, which actively reconstructs the internal space of the net bag according to real-time working conditions, thereby effectively alleviating crushing damage to the catch.

[0007] According to one embodiment of the present invention, the method includes the following steps:

[0008] S1: A distributed sensor array deployed within the trawl net is used to monitor one or more physical parameters in real time, reflecting the degree of fish accumulation inside the net. In one specific embodiment, the distributed sensor array consists of multiple distributed tension sensors, and the physical parameters are the tension values ​​measured at each sensor monitoring point. By analyzing these distributed tension values, the overall magnitude and spatial distribution gradient of the pressure inside the net can be determined.

[0009] S2: The physical parameter data monitored by the distributed sensor array is sent to a central decision and control unit. This unit integrates a preset algorithm model to determine whether the current operating condition meets preset activation conditions. For example, this unit can perform a weighted summation of the physical parameter values ​​received from each monitoring point to calculate a comprehensive crushing risk index I. risk When the index exceeds the preset activation threshold, the activation condition is met.

[0010] S3: Upon meeting preset activation conditions, the central decision and control unit drives a microfluidic regulation unit. This microfluidic regulation unit selectively and controllably pumps ambient seawater into at least one independent region of a partitioned flexible fluid skeleton network. This partitioned flexible fluid skeleton network is also deployed inside the net bag and consists of multiple fluid-isolated independent regions. When seawater is pumped in, the flexible structure constituting the independent region gains temporary stiffness due to the internal fluid pressure, like an inflatable skeleton, forming an effective support structure from inside the net bag to resist external pressure and the weight of the catch, thus alleviating compression.

[0011] The innovation of this invention lies in the establishment of a closed-loop active control system that goes from "real-time perception" to "intelligent decision-making" and then to "zonal execution," which completely changes the traditional passive force-bearing working mode of fishing gear.

[0012] Specifically, in the zonal adjustment step, this method does not perform simple, global pressurization, but rather executes refined, differentiated spatial morphological reconstruction. The central decision-making and control unit can calculate a specific target support pressure for each independent zone requiring adjustment. This target support pressure can be calculated based on the following model:

[0013] P target,j =G j ·max(0,T local,j -T base );

[0014] Among them, P target,j For the target support pressure of the j-th independent region; T local,j It is the local average tension calculated based on sensor data associated with the j-th independent region, reflecting the degree of local pressure in that region; T base It is a preset reference tension, representing the "unloaded" tension of the net bag when there is no significant catch load; G j This is the pressure gain coefficient preset for the j-th independent region, used to convert the tension difference into the required fluid pressure.

[0015] By setting different target support pressures for different areas, the system can differentially pressurize different independent regions of the partitioned flexible fluid skeleton network based on the analyzed pressure distribution gradient. For example, higher pressure is applied to the region with the most severe fish accumulation to obtain the strongest support stiffness, while lower pressure is applied to other regions. In this way, a non-uniform support structure matching the actual pressure distribution is constructed inside the net, forming an "active pressure gradient," thereby making the most efficient use of support force and gently guiding the fish inside, avoiding stress concentration.

[0016] In a preferred embodiment, the method further includes a reset step. After the trawl operation is completed, the central decision and control unit controls the microfluidic adjustment unit to drain seawater from all independent areas of the partitioned flexible fluid skeleton network, restoring the entire system to its initial soft and flat state, facilitating subsequent catch dumping and net handling operations.

[0017] A second aspect of the present invention provides a system for preventing crushing of catches inside trawl nets used in marine fisheries. This system is used to perform the aforementioned method and includes:

[0018] A partitioned flexible fluid skeleton network is deployed inside the trawl net's sac and consists of multiple independent regions that are fluidly isolated from each other.

[0019] A distributed sensor array, deployed within the net bag, is used to monitor in real time one or more physical parameters reflecting the degree of fish stockpiling inside the net bag;

[0020] A microfluidic control unit configured to selectively pump ambient seawater into any one or more independent regions of the partitioned flexible fluidic skeleton network;

[0021] A central decision and control unit is connected to the distributed sensor array and the microfluidic adjustment unit respectively. The central decision and control unit is configured to: receive and process the physical parameter data, determine whether the preset activation conditions are met according to the preset algorithm model, and control the microfluidic adjustment unit to perform partition adjustment operations when the conditions are met.

[0022] This invention provides a method for preventing crushing of catches inside trawl nets in marine fisheries. It has the following beneficial effects:

[0023] 1. Achieves proactive and intelligent protection of catches. This invention integrates a distributed sensor array, a central decision and control unit, and a microfluidic adjustment unit to construct a complete "perception-decision-execution" closed-loop control system. This system can proactively monitor the compression state within the net and automatically respond, fundamentally changing the situation where traditional nets can only passively withstand the compression of catches, and achieving proactive and intelligent protection of catches.

[0024] 2. Significantly improved support efficiency and accuracy. The partitioned flexible fluid skeleton network and its accompanying partitioned target pressure calculation method in this invention can apply differentiated support forces to different areas based on the uneven pressure distribution within the mesh. This "on-demand allocation" support method precisely applies support force to the areas most in need, avoiding energy waste and over-support caused by global uniform pressurization, resulting in more efficient and precise protection.

[0025] 3. High adaptability to dynamically changing operating conditions. The system of this invention can perform continuous cyclical monitoring and dynamic adjustment. As the catch accumulates during trawl operations, the system can periodically reassess the risks and adjust the support pressure in each area, thereby dynamically adapting to changes in the internal state of the net. This high adaptability ensures that the most suitable protection is provided at different stages throughout the entire fishing process.

[0026] 4. Minimal impact on routine trawl operations. When not activated, the partitioned flexible fluid skeleton network has flexible, flat channels that fit snugly against the net, having minimal impact on the hydrodynamic performance of the trawl. During net retrieval, the system is emptied via a reset step, restoring its flexible characteristics without affecting the dumping of the catch or the arrangement of the net, ensuring the system's ease of use.

[0027] 5. Improved system versatility and reliability. By setting algorithm parameters such as weighting coefficients, activation thresholds, and pressure gain coefficients, the system of this invention can be easily adapted and optimized for different trawl net sizes, different target fish species, and different sea conditions, exhibiting good versatility. At the same time, the modular system design facilitates installation, maintenance, and upgrades, improving the overall reliability of the system. Attached Figure Description

[0028] Figure 1 This is a schematic diagram of the method flow of the present invention. Detailed Implementation

[0029] The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0030] refer to Figure 1 This invention provides a method for preventing crushing of catches inside trawls used in marine fisheries, particularly an anti-crushing system for the net bag portion. This system achieves dynamic and proactive management of the internal space of the net bag through an intelligent hardware combination.

[0031] The anti-crushing system primarily comprises four subsystems: a partitioned flexible fluid skeleton network, a distributed sensor array, a microfluidic regulation unit, and a central decision and control unit. These four subsystems are integrated and deployed within the trawl net's mesh layer to form a collaborative and organic whole. The partitioned flexible fluid skeleton network and the distributed sensor array are closely integrated, forming the system's sensing and execution front end. The microfluidic regulation unit and the central decision and control unit are typically integrated within a robust, pressure-resistant, and waterproof housing, fixed in a relatively stable position on the mesh layer, serving as the system's control core.

[0032] In this embodiment, a partitioned flexible fluid skeleton network is woven or fixed to the inner wall surface of the net. This network provides the structural basis for subsequent support. The sensors of the distributed sensing array are precisely mounted at predetermined nodes of the partitioned flexible fluid skeleton network, such as the intersections of longitudinal and circumferential pipes—critical points of stress concentration when the net deforms under stress. This arrangement ensures that any localized tension changes in the net caused by the accumulation of catch can be captured instantly and accurately by the distributed sensing array, providing high-quality raw data input for subsequent monitoring steps.

[0033] The system's signal and control flows are achieved through precise connections. A distributed sensor array transmits the physical parameter signals it collects to the central decision and control unit via waterproof data cables. The central decision and control unit, acting as the system's intelligent hub, is the physical entity that executes the decision-making steps. Upon receiving the data, it analyzes and judges it according to its internally programmed algorithms and generates corresponding control commands. These commands are also sent to the microfluidic regulation unit via electrical signals.

[0034] The microfluidic control unit, serving as the power source for executing the zonal control steps, has multiple fluid outlets connected to each isolated independent region of the zonal flexible fluid skeleton network via a series of flexible pipes. Upon receiving instructions from the central decision and control unit, the microfluidic control unit drives its internal miniature seawater pumps and valve array to precisely pump ambient seawater into the designated independent regions. This series of coordinated actions materializes intangible control commands into a direct and powerful reconstruction of the internal morphology of the network, thereby realizing the core technical concept of this invention.

[0035] In this embodiment, each subsystem constituting the aforementioned anti-crushing system is described in detail to reveal its internal structure and working principle.

[0036] The partitioned flexible fluid skeleton network is the morphological embodiment of this invention. Its skeleton consists of multiple hollow, flat, flexible tubes under normal conditions. To adapt to harsh marine operating environments, these tubes are made of composite materials, such as an inner layer of polyurethane elastomer to ensure airtightness and flexibility, and an outer layer woven with Kevlar or similar high-strength aramid fibers for reinforcement, providing excellent tensile and abrasion resistance. These tubes are carefully arranged inside the mesh, some along the axial (longitudinal) direction, like the ribs of a living organism; others along the radial (circumferential) direction, like hoops. The longitudinal tubes provide primary bending support, while the circumferential tubes effectively prevent excessive radial expansion of the mesh, together forming a stable three-dimensional support cage.

[0037] A key structural feature of this skeletal network lies in its zoned design. The entire network is clearly divided into multiple independent fluid regions, such as the front, middle, and rear zones. This isolation is achieved through physical barriers at the pipe connections between different zones, with each zone connected to the microfluidic control unit only through its dedicated fluid interface. This design transforms the originally singular mesh space into multiple independently adjustable pressure chambers, serving as the prerequisite and physical basis for realizing subsequent zoned dynamic pressure regulation.

[0038] Tightly integrated with the skeleton network is a distributed sensing array. In this embodiment, the array preferably employs a series of highly sensitive piezoelectric tension sensors. These sensors are robustly packaged and fixed to key nodes of the skeleton network, namely the intersections of longitudinal and circumferential channels, which are the core points of stress transmission and concentration when the net is deformed. When the catch inside the net increases and causes compression, the force acting on the net is directly transmitted to the skeleton network, causing significant changes in the tension at these nodes. The piezoelectric sensors can linearly convert these minute changes in mechanical stress into measurable electrical signals, thereby providing the system with accurate raw data on the magnitude and spatial distribution of pressure.

[0039] The microfluidic control unit is the power core for pressure regulation. It mainly consists of a miniature seawater pump and an array of electrically controlled microvalves. The miniature seawater pump can be a high-efficiency miniature gear pump, designed to provide sufficient water pressure and flow rate with low power consumption. The array of electrically controlled microvalves consists of multiple two-position three-way solenoid valves, with each solenoid valve's output port connected one-to-one to an independent area of ​​a partitioned flexible fluid skeleton network. This design gives the central decision and control unit the ability to operate each area independently, including filling, pressurizing, and depressurizing, thereby achieving fine-grained control of fluid direction and flow rate.

[0040] As the intelligent hub of the system, the central decision-making and control unit is integrated into a rugged, pressure-resistant, and waterproof housing. Its core hardware platform includes a high-performance, low-power microcontroller (MCU) responsible for running complex decision-making algorithms; a non-volatile memory for storing program code and key parameters; and multiple data interfaces for receiving signals from the distributed sensor array and sending control commands to the microfluidic regulation unit. To ensure continuous operation throughout the trawling process, the unit is independently powered by a high-energy-density rechargeable lithium-ion battery pack. The overall packaging design of the control unit ensures its long-term stable operation in the high hydrostatic pressure and salt spray corrosion environment of the deep sea.

[0041] The specific implementation process of the method of the present invention will be described in detail below. This process demonstrates the complete closed-loop working process of the system from standby monitoring to active intervention and finally reset.

[0042] In the initial stage of trawl operations, once the net has stabilized in the water and the catch within the net is negligible, the system first executes an initialization procedure. During this stage, the central decision and control unit collects and records tension data from the distributed sensor array. Since the tension at this time is mainly generated by the force of the water flow on the net, the system defines the average tension data collected over a period of time during this stage as the reference tension T. base This reference tension T base It is stored as an important reference value, providing a zero-point benchmark for subsequent judgment of the degree of compression.

[0043] As fishing operations continue, fish begin to accumulate in the nets, and the system then enters a dynamic monitoring and risk assessment phase. Each sensor i in the distributed sensor array continuously reports the measured tension value T. i (t) The data is transmitted in real time to the central decision-making and control unit. Upon receiving this discrete tension data, the control unit calculates the current overall extrusion airflow using the following formula.

[0044] Risk Index I risk (t):

[0045]

[0046] Where n is the total number of sensors, w i These are preset weighting coefficients for each sensor, which reflect...

[0047] The contribution of the sensor's location to the overall crush risk. For example, a sensor located at the very end of the mesh bag has a weight w. i It is usually set higher. The control unit will continuously update the calculated I... risk (t) and a preset activation threshold T a ct is compared. In I r isk(t) is less than T a During CT, the system remains silent and only performs monitoring; once I risk (t) exceeds T act If the compression inside the reticulum has reached a level requiring intervention, the system will immediately initiate the next active adjustment procedure.

[0048] Once the system is activated, its core task is to calculate a precise target support pressure P for each independent region j of the partitioned flexible fluid skeleton network. target,j This process embodies the core intelligence of the invention. First, the control unit extracts tension data from a subset of sensors associated with each region j and calculates the local average tension T of that region. local,j(t). Subsequently, based on the following core control equations, the final target support pressure is calculated:

[0049] P target,j (t)=G j ·max(0,T local,j (t)-T base );

[0050] In this formula, T local,j (t) and reference tension T base The difference accurately reflects the net increase in tension caused by the accumulation of catch. j It is a dimensionless pressure gain coefficient, pre-calibrated based on the structural characteristics of region j (such as pipe diameter, material elastic modulus, etc.). Its function is to convert the physical quantity of net tension into the fluid pressure value required to counteract that tension. This calculation process is performed separately for each independent region, and the result is a series of differentiated target pressure values ​​that accurately map the non-uniform pressure distribution inside the mesh bag.

[0051] After obtaining the target support pressure sequence for each region, the system enters the closed-loop control and spatial morphology reconstruction execution phase. The central decision-making and control unit issues specific instructions to the microfluidic regulation unit, the instructions containing the target pressure value P corresponding to each independent region j. target,j The microfluidic control unit then activates the micro seawater pump and precisely controls its valve array to pump ambient seawater into the corresponding independent areas. Simultaneously with pressurization, the pressure sensor within the pipeline transmits the current pressure P. current,j (t) Feedback is provided to the control unit in real time, forming a tight closed-loop control. When P current,j (t) reaches P target,j At this point, the pressurization process in that area stops and enters a pressure-holding state. Through this series of highly coordinated actions, a support structure with a precise match between stiffness and pressure distribution is constructed inside the originally soft net, i.e., an active pressure gradient, thereby achieving the most optimized and efficient reconstruction of the internal space. Throughout the trawl, the above-mentioned monitoring, evaluation, calculation, and execution steps are repeated periodically, allowing the system's support form to dynamically adapt to the continuous increase in catch. When the fishing operation ends and the trawl is ready to be lifted, the system executes a reset procedure. The central decision and control unit commands the microfluidic adjustment unit to open the pressure relief valves in all areas, and the seawater inside the skeleton net is quickly discharged, restoring the entire structure to its initial, soft, and flat state, which does not affect the dumping of the catch and facilitates the subsequent handling and storage of the net.

[0052] Although embodiments of the invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the appended claims and their equivalents.

Claims

1. A method for preventing crushing of catch inside trawl nets used in marine fisheries, characterized in that, Includes the following steps: S1: Monitoring step, using a distributed sensor array deployed inside the trawl net to monitor in real time one or more physical parameters reflecting the degree of fish accumulation inside the net; S2: Decision-making step, the physical parameter data monitored by the distributed sensor array is sent to a central decision and control unit, which determines whether the preset activation conditions are met according to the preset algorithm model; S3: Zonal adjustment step. If the preset activation conditions are met, the central decision and control unit drives a microfluidic adjustment unit to selectively pump ambient seawater into at least one independent region of a zonal flexible fluid skeleton network. The zonal flexible fluid skeleton network is deployed inside the net bag and consists of multiple isolated independent regions. Pumping seawater gives the flexible structure of the independent region temporary stiffness, thereby forming support from inside the net bag to alleviate the squeezing of the catch.

2. The method according to claim 1, characterized in that, The monitoring steps specifically include: the distributed sensing array is a distributed tension sensor array, and the physical parameter is the tension value of each sensor monitoring point; the central decision and control unit receives the tension value and analyzes it to obtain the pressure distribution gradient inside the mesh bag.

3. The method according to claim 1, characterized in that, The decision-making steps specifically include: the central decision-making and control unit performs a weighted summation of the physical parameter values ​​received from each monitoring point to calculate a comprehensive squeezing risk index; the preset activation condition is: the comprehensive squeezing risk index exceeds a preset activation threshold.

4. The method according to claim 1, characterized in that, In the zonal adjustment step, the central decision and control unit calculates a target support pressure for each independent zone that needs to be adjusted; the target support pressure is calculated based on the physical parameter values ​​of the sensors associated with the independent zone and according to a preset pressure gain function.

5. The method according to claim 4, characterized in that, The formula for calculating the target support pressure is as follows: ; in, For the target support pressure of the j-th independent region, Let J be the pressure gain coefficient for the j-th independent region. The local average tension is calculated based on the sensor data associated with the j-th independent region. The preset reference tension, This is the maximum value.

6. The method according to claim 1, characterized in that, The adjustment process in the zonal adjustment step is a closed-loop feedback process: while the microfluidic adjustment unit pumps seawater into the independent area, the pressure sensor deployed in the pipeline feeds back the current pressure to the central decision and control unit until the current pressure reaches the target support pressure.

7. The method according to claim 1, characterized in that, The partitioned flexible fluid skeleton network is composed of multiple hollow flexible pipes, which are arranged along the longitudinal and circumferential directions of the mesh and fixedly connected to the mesh cover.

8. The method according to claim 1, characterized in that, The microfluidic control unit includes a micro seawater pump and an array of electrically controlled microvalves. Each valve in the array is connected to an independent region of the partitioned flexible fluid skeleton network, and the opening and closing of each valve is independently controlled by the central decision and control unit.

9. The method according to claim 1, characterized in that, The method also includes a reset step: after the trawling operation is completed, the central decision and control unit controls the microfluidic adjustment unit to drain the seawater from all independent areas of the partitioned flexible fluid skeleton network, restoring it to its initial soft and flat state.

10. The method according to any one of claims 1 to 9, characterized in that, The zoning adjustment step further includes: the central decision and control unit, based on the analyzed pressure distribution gradient, differentially pressurizes different independent regions of the zoning flexible fluid skeleton network, so that the skeleton in the region with the most severe fish accumulation obtains the highest support stiffness, thereby constructing a non-uniform support structure inside the net bag that matches the pressure distribution.

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