Trawl Net Position Control for Bathymetry-Responsive Mode Switching
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Solution Overview
Problem
Trawling methods, particularly bottom trawling, cause environmental damage and inefficiencies due to inaccurate position control of trawl nets, leading to ecosystem disruption, high fuel consumption, and undesirable bycatch.
Innovation Solution
Implementing semi-autonomous or autonomous position control systems for trawl nets using sensor data and predictive algorithms to adjust control modes and setpoints, enabling precise navigation and obstacle avoidance, especially in rapidly changing bathymetric conditions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If bottom trawling is used to increase catch quantity, then productivity is improved, but environmental harm increases due to ecosystem damage and bycatch
Solution Approach 1:
The system changes the operational parameters of trawling by using real-time bathymetry data and sensor information to dynamically adjust trawl net position, depth, and orientation. This allows midwater and hybrid trawling methods to achieve high catch quantities while avoiding bottom contact, thereby resolving the contradiction between productivity and environmental harm
Solution Approach 2:
The system implements continuous feedback loops using sensors to monitor trawl net position, depth, and surrounding environment. This feedback enables real-time adjustments to maintain optimal fishing positions without bottom contact, achieving both high productivity and environmental protection through closed-loop control
2Object-affected harmful factors
If midwater trawling is used to reduce environmental impact, then environmental harm is reduced, but position control accuracy deteriorates leading to bottom contact
Solution Approach 1:
The system uses multiple sensors including depth sensors, position sensors, and bathymetry mapping to continuously monitor trawl net position and provide feedback to the control system. This enables accurate position control in midwater trawling operations, preventing bottom contact while maintaining environmental benefits
Solution Approach 2:
The system performs preliminary bathymetry mapping and obstacle detection before trawling operations begin. By having advance knowledge of the seabed topography and obstacles, the system can pre-plan trawl paths and depth profiles that avoid bottom contact, ensuring both environmental protection and position control accuracy
3Ease of operation
If traditional position control is used to simplify operation, then ease of operation is improved, but position control accuracy deteriorates resulting in bottom contact and fuel waste
Solution Approach 1:
The system implements autonomous control capabilities that automatically adjust trawl net position, depth, and orientation based on real-time sensor data and pre-programmed fishing parameters. This self-service automation eliminates the need for complex manual operations while maintaining high position control accuracy, resolving the contradiction between ease of operation and precision
Solution Approach 2:
The system replaces traditional mechanical position control methods with electronic and software-based control systems. Using processors, sensors, and algorithms to control trawl net positioning eliminates the need for complex mechanical adjustment mechanisms, providing both ease of operation and high precision through electronic control
4Use of energy by stationary object
If sensor data frequency is reduced to decrease data processing load, then energy consumption is reduced, but position control performance deteriorates
Solution Approach 1:
The system applies partial data processing by selectively processing only the most critical sensor data at high frequency while processing other data at lower frequencies. This approach maintains position control performance for the most important parameters while reducing overall data processing energy consumption
Solution Approach 2:
The system performs preliminary filtering and preprocessing of sensor data to identify and extract only the most relevant information before full processing. This preliminary action reduces the volume of data requiring intensive processing, thereby reducing energy consumption while maintaining position control performance
Data Source
AI summary
A method of controlling position of a trawl net is provided. The method may comprise: receiving, by a processor, a control input, wherein the control input comprises: (i) a selection of one of a plurality of position control modes, and (ii) a position control setpoint for the trawl net; receiving, by the processor, sensor data indicating a sensed position of the trawl net; generating, by the processor, a first trawl position control output based on the control input and the sensor data; determining, by the processor, a rate of change of bathymetry along a travel path of the trawl net; and in response to the rate of change of bathymetry meeting a threshold condition, generating a second trawl position control output by changing the one of the plurality of position control modes to another of the plurality of position control modes.