Intelligent Optimization Methods and Systems for the Entire Aquaculture Process

Abstract

This invention relates to the fields of underwater acoustic communication and intelligent control technology in aquaculture, and particularly to a method and system for intelligent optimization of the entire aquaculture process cost. The method includes acquiring parameters such as the air supply pressure and water depth of the aeration array; driving an electromagnetic valve to generate a dynamic microbubble refractive grating with a central low-density region; generating a discontinuous acoustic phased array driving timing sequence based on the grating structure evolution period; transmitting an orthogonal frequency division multiplexed signal and extracting the Doppler frequency shift characteristics generated by penetrating the outer high-density region; comparing the characteristics with preset waveguide penetration conditions to generate a high-level trigger quantity; cutting off the power supply to the communication receiving circuit and transferring surplus power quota to the water quality sampling circuit. This invention solves the problem of communication packet loss and retransmission energy consumption caused by aeration bubble interference, achieving energy cost optimization.

Description

Technical Field

[0001] This invention relates to the fields of underwater acoustic communication and intelligent control technology for aquaculture, and particularly to a method and system for intelligent optimization of costs throughout the entire aquaculture process. Background Technology

[0002] Existing intelligent cost optimization technology for the entire aquaculture process is an automated management and control solution with the core objective of reducing overall system energy and material consumption. It relies on a sensor network deployed in the aquatic environment to continuously collect physical and chemical environmental parameters. After receiving these parameters, the central processing unit performs logical comparisons and data analysis, and issues equipment start / stop commands and allocates power quotas to external devices based on a preset algorithm model, thereby effectively reducing equipment idle time and lowering operating electricity costs. The on-demand allocation mechanism relies on establishing a stable two-way data communication link between the underlying sensor nodes and the control center. In offshore operations, a water quality acoustic telemetry system is typically used to construct a cableless communication link to execute tasks such as reporting underlying monitoring data and issuing upper-level oxygenation control commands.

[0003] Existing deep-sea cage acoustic telemetry and intelligent oxygenation linkage control technologies suffer from the following technical challenges: Firstly, the dense microbubble clusters generated after the bottom aeration device is activated lead to strong sound wave scattering and absorption effects. Underwater communication sound waves experience physical attenuation when passing through the dense bubble region, causing a decrease in the signal-to-noise ratio at the receiver and resulting in data decoding failure. Secondly, the frequent retransmission of sound waves by bottom network nodes to complete data delivery consumes a large amount of underwater sensor battery reserves, rendering the global energy consumption control algorithm of the entire communication network ineffective. For example, when a deep-sea dissolved oxygen probe uploads real-time environmental monitoring data to the surface control gateway, the gateway activates the bottom aeration disc upon receiving low-concentration data. The rising bubble curtain generated by the aeration disc significantly increases the acoustic impedance of the ultrasonic uplink transmission path, causing the deep-sea probe to continuously retransmit underwater acoustic telemetry packets due to the lack of acknowledgment. Continuous transmission of ultrasonic signals rapidly depletes the node's battery power, ultimately causing the bottom monitoring network node to go offline and the communication link to be interrupted. Summary of the Invention

[0004] To address the shortcomings of existing technologies, this invention provides a method and system for intelligent cost optimization throughout the entire aquaculture process. This invention solves the technical problem that the high-frequency packet loss of sensors and the sharp increase in power consumption due to node retransmission caused by the severe interference of oxygenation microbubble groups with underwater acoustic communication links leads to the failure of energy cost optimization throughout the entire process.

[0005] To solve the above-mentioned technical problems, the specific contents of the present invention are as follows: In a first aspect, the intelligent cost optimization method for the entire aquaculture process provided by this invention includes: Obtain the air supply pressure parameters of the underwater aeration array and the water depth parameters of the aquatic environment; The voltage control quantity is generated using the air supply pressure parameter and the water depth parameter. The voltage control quantity is used to drive the electromagnetic valve associated with the bottom aeration array, so that the electromagnetic valve outputs a dynamic microbubble refractive grating with the central low-density area and the peripheral high-density area in the vertical space of the water body. Extract the structural evolution period of the dynamic microbubble refractive grating, and generate the discontinuous acoustic phased array driving timing corresponding to the central low-density region based on the structural evolution period; Based on the discontinuous acoustic phased array driven time-series transmission of orthogonal frequency division multiplexing time-domain symbol sequence, the background backscattering Doppler frequency shift characteristics generated by the orthogonal frequency division multiplexing time-domain symbol sequence penetrating the peripheral high-density region are extracted; Compare the background backscattering Doppler frequency shift characteristics with the preset waveguide penetration conditions, and generate a high-level trigger quantity when the comparison result meets the preset waveguide penetration conditions; The power supply to the communication receiving circuit is cut off using the high-level trigger quantity, the surplus power quota is obtained, and the surplus power quota is transferred to the water quality sampling circuit.

[0006] Furthermore, the intelligent cost optimization method for the entire aquaculture process described in this invention, wherein the step of generating a voltage control quantity using the air supply pressure parameter and the water depth parameter, and using the voltage control quantity to drive an electromagnetic valve associated with the bottom aeration array, so that the electromagnetic valve outputs a dynamic microbubble refractive grating with the central low-density area and the peripheral high-density area in the vertical space of the water body, includes: Based on the gas supply pressure parameters and the water depth parameters, a partial differential equation of fluid dynamics space is established and solved to output the fluid dynamics distribution matrix. The fluid dynamics distribution matrix is ​​sliced ​​according to the time dimension to generate a pulse width modulation sequence with time interval attributes; The pulse width modulation sequence is converted into the voltage control quantity, and the electromagnetic valve is driven to open and close according to the voltage control quantity in a set sequence, so as to output the dynamic microbubble refractive grating with the central low-density area and the peripheral high-density area in the vertical space of the water body.

[0007] Furthermore, in the intelligent optimization method for the entire aquaculture process cost of the present invention, the extraction of the structural evolution period of the dynamic microbubble refractive grating includes: A probe pilot signal is emitted to the dynamic microbubble refractive grating; The backscattered sound waves generated after the probe pilot signal is incident on the peripheral high-density area are extracted, and the backscattered sound waves are converted into a discrete digital matrix; The discrete digital matrix is ​​subjected to envelope detection operation to output the spatial gradient distribution matrix of the sound wave reflection intensity; A peak detection algorithm is applied to the spatial gradient distribution matrix to extract the coordinates of the minimum decay values ​​in the spatial gradient distribution matrix. The coordinate point of the minimum attenuation value is set as the center position within the central low-density region, and the value of the center position changing over time is extracted as the structural evolution period.

[0008] Furthermore, the intelligent cost optimization method for the entire aquaculture process described in this invention, wherein generating the discontinuous acoustic phased array driving timing sequence corresponding to the central low-density region based on the structural evolution cycle, includes: Extract the spatial coordinates of the center position; Based on the relative geometric position of the spatial coordinate point and the signal transmitting end, perform spatial trigonometric function calculations and output relative angle parameters; The phase delay time parameter of the independent transmitting element in the acoustic wave transmitting array is calculated based on the relative angle parameter. The phase delay time parameter is used to generate the driving timing of the discontinuous acoustic phased array that matches the central low-density region.

[0009] Furthermore, in the intelligent cost optimization method for the entire aquaculture process described in this invention, the transmitted orthogonal frequency division multiplexing time-domain symbol sequence includes: Collect the digital value of dissolved oxygen concentration output by the water quality sampling circuit; The digital value of dissolved oxygen concentration is mapped to complex constellation points using quadrature amplitude modulation logic. Perform an inverse fast Fourier transform operation on the complex constellation points to generate the orthogonal frequency division multiplexing time-domain symbol sequence; Obtain the hardware system timestamp, and align the continuous transmission time window of the orthogonal frequency division multiplexing time domain symbol sequence with the time period of the central low-density area based on the underlying timestamp.

[0010] Furthermore, the intelligent cost optimization method for the entire aquaculture process described in this invention, wherein the extraction of the background backscattering Doppler frequency shift features generated by the orthogonal frequency division multiplexing time-domain symbol sequence penetrating the peripheral high-density region, includes: The orthogonal frequency division multiplexing time-domain symbol sequence is converted into a mechanical vibration signal and radiated into the water body according to the discontinuous acoustic phased array driven timing-driven acoustic wave transmitting array. The mechanical vibration signal is received, penetrates the central low-density region, and undergoes fluid interface scattering with the peripheral high-density region, generating a scattered echo; A fast Fourier transform is performed on the scattered echo, and the frequency domain peak value is extracted as the background backscattering Doppler frequency shift feature.

[0011] Furthermore, the intelligent cost optimization method for the entire aquaculture process described in this invention, wherein comparing the background backscattering Doppler frequency shift characteristics with preset waveguide penetration conditions, and generating a high-level trigger quantity when the comparison result meets the preset waveguide penetration conditions, and using the high-level trigger quantity to cut off the power supply to the communication receiving circuit, includes: Extract the center frequency of the frequency shift contained in the background backscattering Doppler frequency shift feature; Compare the frequency shift center frequency with the frequency offset extreme values ​​included in the preset waveguide penetration condition; When the frequency shift center frequency reaches the frequency deviation extreme value, the high-level trigger value is output; The high-level trigger signal drives the solid-state switch circuit to disconnect the power supply circuit of the communication receiving circuit, thereby cutting off the power supply to the communication receiving circuit.

[0012] Furthermore, in the intelligent cost optimization method for the entire aquaculture process described in this invention, the step of obtaining surplus electricity quotas and transferring the surplus electricity quotas to the water quality sampling circuit includes: After cutting off the power supply to the communication receiving circuit, the preset response waiting time and the listening operating current of the communication receiving circuit are extracted. Multiply the preset response waiting time by the listening current to output the standby power value; The standby power value is analyzed and calculated using power allocation logic to generate a compensation power supply pulse width that matches the water quality sampling circuit; The compensation power supply pulse width is determined as the surplus power quota, and the energy distribution network is reconstructed at the underlying hardware level to transfer the surplus power quota to the water quality sampling circuit.

[0013] Furthermore, the intelligent cost optimization method for the entire aquaculture process described in this invention, after obtaining surplus power quotas and transferring the surplus power quotas to the water quality sampling circuit, includes: The water quality sampling circuit is driven to increase the sampling frequency by utilizing the transferred surplus power quota, and to collect and output a high-frequency digital quantity of dissolved oxygen concentration. The high-frequency dissolved oxygen concentration digital quantity is encapsulated into a data frame to generate an environmental water quality data packet, which is then buffered and output. Extract the characteristic concentration values ​​from the environmental water quality data package and compare the characteristic concentration values ​​with a preset safe concentration threshold. When the characteristic concentration value reaches the preset safe concentration threshold, a duty cycle decay command is generated, and the opening and closing duty cycle of the solenoid valve is reduced by the duty cycle decay command.

[0014] Secondly, the intelligent optimization system for the entire aquaculture process cost provided by this invention, applied to the aforementioned intelligent optimization method for the entire aquaculture process cost, includes: The parameter acquisition module is used to acquire the air supply pressure parameters of the underwater aeration array and the water depth parameters of the aquatic environment. The grating generation module is used to generate a voltage control quantity using the air supply pressure parameter and the water depth parameter, and use the voltage control quantity to drive the electromagnetic valve associated with the bottom aeration array, so that the electromagnetic valve outputs a dynamic microbubble refractive grating with the central low-density area and the peripheral high-density area in the vertical space of the water body. The timing generation module is used to extract the structural evolution period of the dynamic microbubble refractive grating and generate a discontinuous acoustic phased array driving timing corresponding to the central low-density region based on the structural evolution period. The feature extraction module is used to extract the background backscattering Doppler frequency shift features generated by the orthogonal frequency division multiplexing time-domain symbol sequence transmitted by the discontinuous acoustic phased array driving the timing transmission of the orthogonal frequency division multiplexing time-domain symbol sequence through the peripheral high-density region. The trigger quantity generation module is used to compare the background backscattering Doppler frequency shift characteristics with the preset waveguide penetration conditions, and generate a high-level trigger quantity when the comparison result meets the preset waveguide penetration conditions. The quota transfer module is used to cut off the power supply to the communication receiving circuit by using the high-level trigger quantity, obtain the surplus power quota, and transfer the surplus power quota to the water quality sampling circuit.

[0015] Beneficial effects of this invention: This invention provides a method and system for intelligent cost optimization throughout the entire aquaculture process. It utilizes air supply pressure and water depth parameters to generate voltage control quantities, driving an electromagnetic valve associated with an underwater aeration array to output a dynamic microbubble refractive grating with a central low-density region and an outer high-density region in the vertical space of the water body. This actively constructs a fluid medium channel at the physical level to guide the convergence and transmission of sound waves. The system extracts the structural evolution period of the dynamic microbubble refractive grating and generates a discontinuous acoustic phased array driving timing sequence corresponding to the central low-density region based on the structural evolution period. According to the discontinuous acoustic phased array driving timing sequence, an orthogonal frequency division multiplexing (OFDM) time-domain symbol sequence is emitted, guiding underwater communication sound waves to physically penetrate the central low-density region, significantly reducing the physical attenuation effect that occurs when sound waves penetrate the microbubble cluster. The system extracts the background backscattering Doppler frequency shift characteristics generated when the OFDM time-domain symbol sequence penetrates the outer high-density region, and generates a high-level trigger quantity when the comparison result meets the preset waveguide penetration conditions. By directly cutting off the power supply to the communication receiving circuit using a high-level trigger, the excessive and ineffective power consumption caused by frequent acoustic retransmissions from underlying network nodes is prevented through hardware-level power-off. The power supply network acquires the surplus power quota generated by the power cut and transfers it to the water quality sampling circuit, physically transferring the power saved in the communication link to the high-frequency acquisition of environmental parameters. This closed-loop mechanism, connecting the acoustic transmission pattern with the energy allocation of underlying nodes, effectively solves the technical problem of high-frequency packet loss and a sharp increase in power consumption due to node retransmission caused by interference from oxygenation microbubble swarms in the underwater acoustic communication link. Attached Figure Description

[0016] To more clearly illustrate the technical solution of the present invention, the drawings used in the embodiments will be briefly introduced below. Obviously, for those skilled in the art, other drawings can be obtained based on the drawings without creative effort.

[0017] Figure 1 This is a flowchart of the intelligent cost optimization method for the entire aquaculture process according to the present invention. Detailed Implementation

[0018] To make the technical solution of the present invention clearer, the present invention will be clearly and completely described below with reference to specific embodiments and corresponding drawings. Obviously, the described embodiments are only a part of the embodiments of the present invention, and not all of them. 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. The various embodiments of the present invention will be described in detail below with reference to the accompanying drawings. To better understand the purpose of the present invention, the present invention will be described in further detail below.

[0019] Firstly, please refer to Figure 1The intelligent cost optimization method for the entire aquaculture process provided by this invention includes: Step 1: Obtain the air supply pressure parameters of the underwater aeration array and the water depth parameters of the aquatic environment; Step 2: Use the air supply pressure parameter and the water depth parameter to generate a voltage control quantity, and use the voltage control quantity to drive the electromagnetic valve associated with the bottom aeration array, so that the electromagnetic valve outputs a dynamic microbubble refractive grating with the central low-density area and the outer high-density area in the vertical space of the water body. Step 3: Extract the structural evolution period of the dynamic microbubble refractive grating, and generate the discontinuous acoustic phased array driving timing corresponding to the central low-density region based on the structural evolution period. Step 4: Based on the orthogonal frequency division multiplexing time-domain symbol sequence driven by the discontinuous acoustic phased array, extract the background backscattering Doppler frequency shift characteristics generated by the orthogonal frequency division multiplexing time-domain symbol sequence penetrating the peripheral high-density region; Step 5: Compare the background backscattering Doppler frequency shift characteristics with the preset waveguide penetration conditions, and generate a high-level trigger quantity when the comparison result meets the preset waveguide penetration conditions; Step 6: Use the high-level trigger quantity to cut off the power supply to the communication receiving circuit, obtain the surplus power quota, and transfer the surplus power quota to the water quality sampling circuit.

[0020] In the application environment of automated monitoring and oxygenation linkage for deep-sea cages, the data acquisition terminal obtains the air supply pressure parameters of the underwater aeration array and the water depth parameters of the aquatic environment. After receiving the air supply pressure parameters and water depth parameters, the processing center establishes a partial differential equation in the fluid dynamics space and performs partial differential numerical solution calculations, transforming the underlying physical environment state into a fluid dynamics distribution matrix at the data level. The computing engine performs time window slicing calculations on the fluid dynamics distribution matrix according to the time dimension, generating a pulse width modulation sequence with time interval attributes. The underlying driver board converts the pulse width modulation sequence into an analog voltage control quantity on the control cable, and drives the electromagnetic valves associated with the underwater aeration array to mechanically open and close according to the set timing based on the voltage control quantity. The regular action of the electromagnetic valves outputs a dynamic microbubble refractive grating with a central low-density area and an outer high-density area in the vertical space of the water body, thereby artificially reconstructing the physical transmission medium environment of underwater acoustic communication.

[0021] The bottom-layer probe transducer emits a high-frequency probe pilot signal to the dynamic microbubble refractive grating. The analog front-end component extracts the backscattered acoustic waves generated by the acoustic scattering of the probe pilot signal upon contact with the surrounding high-density area. These backscattered acoustic waves are then input to an analog-to-digital converter (ADC) to be converted into a discrete digital matrix. The digital signal processing chip performs envelope detection on the discrete digital matrix, eliminating high-frequency carrier components and outputting a spatial gradient distribution matrix characterizing the acoustic wave reflection intensity. The logic unit executes a peak detection algorithm on the spatial gradient distribution matrix, utilizing the zero-crossing feature of the derivative to extract the coordinates of the attenuation minimum points in the spatial gradient distribution matrix. In the peak detection algorithm processing stage of the logic unit, to achieve the conversion of underwater acoustic physical characteristics to digital spatial coordinates, the specific input data format, output data format, and internal computational logic of the peak detection algorithm are defined. The input data of the peak detection algorithm is the spatial gradient distribution matrix of the acoustic wave reflection intensity output after envelope detection processing. This spatial gradient distribution matrix carries the continuous acoustic intensity amplitude characteristics in the corresponding three-dimensional physical space coordinate system. The specific data processing path is as follows: Gaussian smoothing filtering is performed on the input spatial gradient distribution matrix to filter out non-target high-frequency noise data caused by irregularly suspended particles in the water; the first and second spatial partial derivative matrices of the smoothed matrix on the preset three-dimensional coordinate axes are calculated; the data nodes inside the smoothed matrix are traversed, and data nodes with zero first spatial partial derivatives and positive second spatial partial derivatives are extracted and included in the candidate minimum set; the acoustic reflection intensity amplitude of each data node in the candidate minimum set is compared with the preset lower limit threshold for reflection amplitude, and pseudo-feature points below the preset lower limit threshold are eliminated. Data nodes that meet the constraints are extracted, and the three-dimensional spatial coordinate data of the corresponding constrained data nodes are output as the coordinate points of the attenuation minimum. The aforementioned physical feature extraction and algorithm threshold screening logic constructs an intrinsic correlation mapping between the background acoustic parameters of the underwater dynamic bubble sparse region and the underlying communication coordinate position, providing a basic input source for the subsequent mathematical planning of the acoustic wave directional waveguide transmission path.

[0022] The system sets the coordinate point of the minimum attenuation value as the physical center position within the central low-density zone. By continuously recording the coordinate point sequence, the system extracts the periodic time difference value of the center position changing over time as the structural evolution period, thus completing the digital spatiotemporal mapping of the fluid dynamic characteristics.

[0023] The central processing unit extracts the three-dimensional spatial coordinates of the center location. The geometry calculation unit performs spatial trigonometric function calculations based on the relative geometric position of the spatial coordinates and the signal transmitter, calculating the three-dimensional Euler angles and outputting relative angle parameters indicating the directional convergence path of the acoustic waves. The microcontroller calculates the phase delay time parameters between the independent transmitting elements in the acoustic wave transmitting array based on the relative angle parameters. The beamforming logic uses the phase delay time parameters to generate a discontinuous acoustic phased array drive timing sequence that matches the penetration characteristics of the central low-density area. In the synchronous data processing channel, the bottom-level nodes acquire the dissolved oxygen concentration digital value output in real time from the water quality sampling circuit. The baseband processor uses orthogonal amplitude modulation logic to map the dissolved oxygen concentration digital value to the argument characteristics on complex constellation points, performs an inverse fast Fourier transform operation on the complex constellation points, and generates an orthogonal frequency division multiplexing (OFDM) time-domain symbol sequence. The clock synchronization module obtains the underlying hardware timestamp and, based on the underlying timestamp, aligns the continuous transmission time window of the OFDM time-domain symbol sequence with the time period of the central low-density area for directional transmission.

[0024] The transmitting drive circuit drives the acoustic wave transmitting array according to the timing sequence of the discontinuous acoustic phased array, converting the orthogonal frequency division multiplexing time-domain symbol sequence into a mechanical vibration signal and radiating it into the water. The underwater listening probe receives the mechanical vibration signal, penetrates the central low-density area, and generates frequency-offset scattered echoes derived from fluid boundary friction in the surrounding high-density area. The microprocessor performs a fast Fourier transform on the scattered echoes, extracts the energy peaks in the frequency domain distribution spectrum as the background backscattering Doppler frequency shift feature, and extracts the frequency shift center frequency contained in the background backscattering Doppler frequency shift feature from the frequency domain results. The logic comparator compares the frequency shift center frequency with the frequency offset extreme value contained in the preset waveguide penetration condition. When the frequency shift center frequency reaches the frequency offset extreme value, the general-purpose input / output port immediately outputs a high-level trigger signal. The power control center uses the high-level trigger signal to directly drive the solid-state switching circuit to disconnect the power supply circuit of the communication receiving circuit, thereby completely blocking the power supply to the communication receiving circuit at the physical link layer.

[0025] After the power supply to the communication receiving circuit is cut off, the status register extracts the original preset response waiting time and the listening current of the communication receiving circuit. The arithmetic logic unit multiplies the preset response waiting time and the listening current, and outputs the standby power value representing the idle power consumption. The power allocation logic analyzes the standby power value and generates the compensation power pulse width required for the frequency upscaling of the water quality sampling circuit through digital-to-analog control proportional conversion. In order to clarify the specific data mapping and intrinsic correlation of the power allocation logic in the underlying hardware energy reconfiguration scenario, the input data of the power allocation logic algorithm is set to the standby power value and the real-time operating voltage of the underlying DC power supply bus, and the output data is the compensation power pulse width of the switching transistor in the voltage regulator circuit. The specific data processing path and internal calculation steps are as follows: The power allocation logic multiplies the standby power value with the real-time operating voltage to obtain the absolute surplus energy value accumulated when the communication receiving circuit stops listening; the basic energy consumption calibration parameters of the analog-to-digital conversion component inside the water quality sampling circuit within a single sampling cycle are extracted; the absolute surplus energy value is divided by the basic energy consumption calibration parameters to calculate the total number of additional discrete sampling points allowed by physical conditions within the current oxygenation cycle; the target sampling increment frequency is obtained by dividing the total number of additional discrete sampling points by the duration of the oxygenation cycle; the target sampling increment frequency is mapped to the corresponding target driving current value according to the current load characteristic curve of the hardware power supply system; the target driving current value is substituted into the proportional-integral-derivative control algorithm model as a reference input, and combined with the closed-loop feedback value of the current bus voltage, the duty cycle of the driving waveform used to maintain the target driving current is calculated; finally, the duty cycle of the driving waveform is converted into the compensation power supply pulse width. The aforementioned algorithm steps construct an accurate mathematical transfer function for the power supply drive signal from the idle physical power of the communication terminal to the water quality detection terminal, eliminating the uninterpretability in the numerical conversion process and enabling the system to achieve an objective physical mapping of local energy consumption scheduling data in accordance with the principle of energy conservation.

[0026] The power supply scheduling node determines the surplus power quota by the compensation power supply pulse width and reconstructs the energy distribution network, including the switching power supply and voltage regulation circuit, at the underlying hardware level. This surplus power quota is then losslessly transferred to the water quality sampling circuit. The system drives the water quality sampling circuit to increase the sampling frequency of the analog-to-digital converter using the transferred surplus power quota, acquiring and outputting a high-frequency digital value of dissolved oxygen concentration. The communication framing logic encapsulates the high-frequency dissolved oxygen concentration digital value into a data frame containing a header and checksum, generating an environmental water quality data packet and buffering it in the physical memory. The control and analysis center extracts the characteristic concentration value from the environmental water quality data packet and compares it with a preset safe concentration threshold that meets the lower limit of the dissolved oxygen standard. When the characteristic concentration value reaches the preset safe concentration threshold, the pulse controller generates a duty cycle attenuation command, which directly controls the high-power switching transistor to reduce the mechanical opening and closing duty cycle of the solenoid valve.

[0027] In the processing stage where the partial differential equations of fluid dynamics are established based on the supply pressure parameters and water depth parameters, and the fluid dynamics distribution matrix is ​​output through solution calculation, the processing center inputs the supply pressure parameters and water depth parameters as initial boundary conditions into the partial differential equations of fluid dynamics. The specific expression of the partial differential equations of fluid dynamics is as follows:

[0028] In the formula, The microbubble density function represents the density of microbubbles in the three-dimensional spatial coordinate system of the water body. The partial derivative of the microbubble density function with respect to time is denoted as . Represents the gradient operator in three-dimensional space. Represents the water flow velocity vector. The convective divergence term represents the density of microbubbles. This represents the diffusion coefficient of microbubbles in water. Represents the Laplace operator, The diffusion term representing the density of microbubbles, This represents the gas supply pressure parameter. Represents water depth parameters. This represents the bubble source term, which consists of air supply pressure parameters and water depth parameters. The computation engine uses a finite difference algorithm to discretize and solve the partial differential equations in the fluid dynamics space, calculates the microbubble density values ​​at the discrete spatial grid points, arranges the microbubble density values ​​according to spatial coordinates, and directly outputs the fluid dynamics distribution matrix.

[0029] In the processing stage where spatial trigonometric functions are performed to calculate relative angle parameters based on the relative geometric positions of the spatial coordinate points and the signal transmitter, the geometric calculation unit extracts the three-dimensional spatial coordinate points of the center position and the three-dimensional reference coordinate points of the signal transmitter. The relative angle parameters include the horizontal azimuth angle and the vertical pitch angle. The specific formulas for solving the spatial trigonometric functions are as follows:

[0030] In the formula, Represents the vertical pitch angle in the relative angle parameters. Represents the inverse cosine function. The coordinate components of the three-dimensional spatial point representing the center location on the vertical Z-axis. The coordinate components of the three-dimensional reference coordinate point at the signal transmitter on the vertical Z-axis. The coordinate components of the three-dimensional spatial coordinate point representing the center location on the horizontal X-axis. The coordinate components of the three-dimensional reference coordinate point of the signal transmitter on the horizontal X-axis. The coordinate components of the three-dimensional spatial point representing the center location on the horizontal Y-axis. The coordinate components of the three-dimensional reference coordinate point of the signal transmitter on the horizontal Y-axis; This represents the three-dimensional Euclidean distance between the center location and the signal transmitter. This represents the horizontal azimuth angle in the relative angle parameters. This represents the arctangent function. The geometric operation unit extracts the coordinate difference and substitutes it into the inverse trigonometric function for algebraic calculation, outputting the vertical pitch angle and horizontal azimuth angle, which are then combined to form the relative angle parameters.

[0031] In the processing step of calculating the phase delay time parameter of the independent transmitting elements in the acoustic wave transmitting array based on the relative angle parameter, the microcontroller reads the intra-array relative coordinates of the independent transmitting elements in the acoustic wave transmitting array and performs phase compensation numerical calculation using the relative angle parameter. The specific calculation formula for the phase delay time parameter is as follows:

[0032] In the formula, Represents the first in the acoustic wave emitting array Phase delay time parameters of each independent transmitting element, Representing the The relative coordinate components within the array of each independent transmitting element on the horizontal X-axis. Representing the The relative coordinate components within the array of each independent transmitting element on the horizontal Y-axis. Representing the The relative coordinate components within the array of each independent transmitting element on the vertical Z-axis. Represents the vertical pitch angle in the relative angle parameters. This represents the horizontal azimuth angle in the relative angle parameters. The sine value representing the vertical pitch angle. The cosine value representing the horizontal azimuth angle. The sine value representing the horizontal azimuth angle. The cosine value representing the vertical pitch angle. This represents the constant speed of sound propagation in water. The microcontroller calculates the spatial geometric projection distance and divides it by the constant speed of sound propagation in water to obtain the time difference for each independent transmitting element to perform a delayed transmission action, and assigns this time difference value to the phase delay time parameter. In the processing step of extracting the preset response waiting time and the listening current of the communication receiving circuit, and multiplying the preset response waiting time by the listening current to output the standby power value, the arithmetic logic unit reads the physical values ​​from the system configuration register of the communication receiving circuit and performs a linear multiplication operation. The specific calculation formula is as follows:

[0033] In the formula, This represents the standby battery level. This represents the preset response waiting time. Represents the current used for listening. This represents the multiplication operator. After the arithmetic logic unit completes the product operation, it inputs the standby power value, representing the energy consumed, into the power allocation logic for subsequent pulse width conversion.

[0034] The physically collected data were then substituted into all the aforementioned calculation and processing steps for overall implementation verification. Water depth parameters of the aquatic environment were set. Set the air supply pressure parameters for the underwater aeration array to 20 meters. The pressure is 300 kPa. The processing center inputs the 20-meter water depth parameter and the 300 kPa air supply pressure parameter into the partial differential equation of fluid dynamics, and outputs the corresponding fluid dynamic distribution matrix after finite difference solution. The geometric calculation unit extracts the coordinate components of the three-dimensional spatial coordinate point at the center position on the horizontal X-axis. The coordinate components of 15 meters on the horizontal Y-axis The coordinate components of 20 meters on the vertical Z-axis The distance is 10 meters. Extract the coordinate components of the three-dimensional reference coordinate point of the signal transmitter on the horizontal X-axis. Coordinate components of 5 meters on the horizontal Y-axis Coordinate components of 10 meters on the vertical Z-axis The value is 0 meters. The three-dimensional spatial coordinate components are input into the spatial trigonometric function solution formula to calculate the vertical pitch angle in the relative angle parameters. The horizontal azimuth angle is calculated from the relative angle parameter of 0.955 radians. The value is 0.785 radians. The microcontroller extracts the intra-array relative coordinate components of the first independent transmitting element on the horizontal X-axis. The relative coordinate components within the matrix on the horizontal Y-axis are 0.1 meters. The relative coordinate components within the matrix, 0.1 meters in length, on the vertical Z-axis. Set the depth to 0 meters and the speed of sound in water to a constant. The value is 1500 meters per second. The relative coordinate components within the array, the relative angle parameters, and the constant velocity of sound waves in water are input into the phase delay time parameter calculation formula to obtain the phase delay time parameter of the first independent transmitting element. The time is 0.000076 seconds. The arithmetic logic unit extracts the preset response waiting time of the communication receiving circuit. Extract the listening current for 5 seconds. The current is 0.02 amps. Multiply the preset 5-second response wait time by the 0.02 amps listening current input in the power calculation formula to obtain the standby power value. The standby power value is 0.1 coulombs. The power allocation logic receives the 0.1 coulomb standby power value, converts it into an equivalent compensation power supply pulse width, and drives the underlying hardware to reconfigure the energy distribution network and transfer it to the water quality sampling circuit.

[0035] In the computation phase of the proportional-integral-derivative (PID) control algorithm model for power distribution logic, the computation engine constructs the PID model based on a closed-loop feedback mechanism. The computation engine sets the target drive current value as the reference input for the PID model, while the control center collects the actual operating current feedback from the voltage regulator circuit output in real time via a current transformer. The logic comparator calculates the difference between the target drive current value and the actual operating current feedback, outputting the real-time current error value. The proportional operation unit multiplies the real-time current error value by the system-calibrated proportional gain coefficient, outputting the proportional control component for immediate response to dynamic deviations. The integral operation unit performs an integral operation on the real-time current error value along the time dimension, multiplies the result by the integral time constant, and outputs the integral control component for eliminating steady-state error. The derivative operation unit calculates the rate of change of the real-time current error value, multiplies the rate of change by the derivative time constant, and outputs the derivative control component for suppressing current overshoot oscillations. The data adder linearly superimposes the proportional control component, integral control component, and derivative control component to generate a comprehensive control signal. The pulse width modulator receives the integrated adjustment signal and maps it to the duty cycle of the drive waveform that controls the on-time of the switching transistor. The computing engine establishes a precise mathematical mapping relationship between the target drive current value and the drive waveform duty cycle by merging the three control components.

[0036] In the process of executing physical feature extraction and state determination logic, the central processing unit (CPU) sets specific threshold parameters for various related parameters of the system's internal operation. For the preset lower limit of reflection amplitude, researchers calibrated it based on underwater environmental noise and equipment background electrical noise, and the CPU fixed the preset lower limit of reflection amplitude at -65 dB. The digital signal processing chip directly eliminates pseudo-feature points with reflection amplitudes below -65 dB, retaining the coordinates of the true minimum attenuation values ​​with reflection amplitudes above -65 dB. For the frequency offset extremes included in the preset waveguide penetration conditions, the signal analysis module establishes a parameter benchmark based on the relative Doppler relationship between the microbubble rise velocity and the sound wave frequency, and sets the frequency offset extremes to ±50 Hz. When the logic comparator determines that the absolute value of the center frequency of the received signal's frequency shift is greater than 50 Hz, the logic comparator immediately outputs a high-level trigger signal. For the preset safe concentration threshold, the system's main control chip sets baseline parameters based on the biological oxygen demand characteristics of the cultured aquatic products, and sets the preset safe concentration threshold to 5.5 mg / L. The water surface control center compares the extracted characteristic concentration values ​​with a baseline of 5.5 mg / L. When the characteristic concentration value exceeds 5.5 mg / L, it sends a duty cycle decay command to the lower-level nodes. The system's built-in fixed parameter loading ensures that the logical comparison operation has clear mathematical boundaries.

[0037] Secondly, the intelligent optimization system for the entire aquaculture process cost provided by this invention, applied to the aforementioned intelligent optimization method for the entire aquaculture process cost, includes: The parameter acquisition module is used to acquire the air supply pressure parameters of the underwater aeration array and the water depth parameters of the aquatic environment. The grating generation module is used to generate a voltage control quantity using the air supply pressure parameter and the water depth parameter, and use the voltage control quantity to drive the electromagnetic valve associated with the bottom aeration array, so that the electromagnetic valve outputs a dynamic microbubble refractive grating with the central low-density area and the peripheral high-density area in the vertical space of the water body. The timing generation module is used to extract the structural evolution period of the dynamic microbubble refractive grating and generate a discontinuous acoustic phased array driving timing corresponding to the central low-density region based on the structural evolution period. The feature extraction module is used to extract the background backscattering Doppler frequency shift features generated by the orthogonal frequency division multiplexing time-domain symbol sequence transmitted by the discontinuous acoustic phased array driving the timing transmission of the orthogonal frequency division multiplexing time-domain symbol sequence through the peripheral high-density region. The trigger quantity generation module is used to compare the background backscattering Doppler frequency shift characteristics with the preset waveguide penetration conditions, and generate a high-level trigger quantity when the comparison result meets the preset waveguide penetration conditions. The quota transfer module is used to cut off the power supply to the communication receiving circuit by using the high-level trigger quantity, obtain the surplus power quota, and transfer the surplus power quota to the water quality sampling circuit.

[0038] In this invention, the dynamic microbubble refractive grating refers to a specific fluid physics structure formed in water by a controlled microbubble swarm generated by an underwater aeration array. This structure is not a physical grating in the traditional optical sense, but rather refers to the alternating formation of low-bubble-density and high-bubble-density regions within the fluid space during the microbubble's ascent, controlled by pulses from electromagnetic valves. Because the sound velocity and acoustic impedance differ in water bodies with varying bubble densities, this periodically distributed bubble density gradient acts similarly to the refraction and waveguide constraint of a grating on underwater sound waves, thereby guiding the sound waves to converge and propagate directionally along the low-density region.

[0039] Discontinuous acoustic phased array drive timing specifically refers to a particular electronic drive time sequence used to control the emission action of an underwater acoustic transducer array. Excitation refers to the electroacoustic conversion drive or emission action of the transducer; discontinuous means that the drive timing is not continuously generated, but rather intermittently and aligned based on the periodic occurrence of the central low-density region in the aforementioned dynamic bubble curtain. This timing controls the phase delay time between each independent transmitting element, enabling the acoustic beam to be precisely aligned and penetrate the low-density bubble channel.

[0040] The background backscattering Doppler frequency shift refers to the frequency shift of the acoustic echo generated when a sound wave signal propagates in water and encounters the interface of a high-density bubble swarm. Here, "background" does not refer to conventional ambient noise, but specifically to the reference Doppler frequency shift of the background echo returning to the receiver after the sound wave undergoes physical friction or collision with the fluid boundary and the dynamic microbubble swarm. This characteristic reflects the relative physical modulation effect of the rising bubble curtain on the sound wave frequency.

[0041] Fluid interface reflection refers to the acoustic reflection or scattering phenomenon that is excited or generated when a sound wave propagates underwater and comes into contact with the interface between high-density microbubbles and low-density water (i.e., the interface of abrupt change in acoustic impedance). Fluid interface reflection refers to the physical continuous process by which the initial incident sound wave interacts with the physical interface of the bubble curtain and is converted into secondary backscattered sound waves.

[0042] Mathematical boundary limits refer to specific numerical thresholds or judgment ranges set for preset parameters (such as the lower limit threshold of reflection amplitude, frequency offset extreme value, safe concentration threshold, etc.) during system logic control and algorithm judgment. The system triggers corresponding hardware switching actions based on the numerical thresholds or judgment ranges.

[0043] Compensated power supply pulse width essentially refers to the duty cycle duration of the pulse width modulation (PWM) signal that controls the on-time of the switching transistor in a switching power supply circuit. It maps the calculated duty cycle ratio to the actual duration of the driving level executed by the underlying hardware circuit, in seconds or microseconds.

[0044] Product operation refers to the mathematical multiplication operation performed by the arithmetic logic unit within a microprocessor on two parameters with different physical dimensions (such as preset response waiting time and listening current). The output of the product operation represents the amount of charge or the standby power consumption, realizing the conversion between physical parameters.

[0045] The absolute surplus energy value refers to the actual remaining electrical energy that the system saves and can allocate after the power supply to the communication receiving circuit is cut off by a physical hardware switch. This value excludes the basic background losses during system operation and represents the total available surplus electrical energy that can be fully extracted and transferred without loss to the water quality sampling circuit to increase the sampling frequency within the current oxygenation cycle.

[0046] Partial differential equations in fluid dynamics refer to the partial differential governing equations commonly used in this field to describe the state of fluid mechanics. In this paper, the equation is mainly used to solve for the distribution gradient of the microbubble density function in a three-dimensional spatial coordinate system (x, y, z), thereby constructing a three-dimensional fluid dynamics distribution matrix that reflects the variation of microbubble density with water depth and spatial position.

[0047] High-frequency packet loss refers to the phenomenon where a high percentage of data packets are lost or fail to be decoded per unit time when an underwater acoustic communication link is subjected to strong scattering interference from a dense cluster of microbubbles. It reflects an extreme state of obstruction caused by the deterioration of the physical channel, resulting in a surge in the interruption rate of the underwater acoustic communication network and a data delivery success rate significantly lower than the system's preset communication baseline.

[0048] The underlying timestamp refers to the time reference data with high-precision synchronization capabilities generated by the Media Access Control (MAC) layer or physical layer clock module of the underwater hardware system. The system uses this timestamp to realize the orthogonal frequency division multiplexing time domain symbol transmission window of the communication node, which can achieve precise physical alignment with the occurrence period of the low-density region at the center of microbubbles in the fluid environment.

[0049] Surplus power quota refers to the unplanned available power intercepted by the system when it actively cuts off the power supply to the communication receiving circuit after detecting that the acoustic channel is blocked by bubbles. In energy-constrained underwater battery-powered networks, this portion of power, which would otherwise be consumed by invalid communication retransmissions, is treated as a dispatchable surplus power and allocated to the water quality sampling circuit to drive it to perform high-frequency sampling tasks.

Claims

1. A method for intelligent optimization of costs throughout the entire aquaculture process, characterized in that, include: Obtain the air supply pressure parameters of the underwater aeration array and the water depth parameters of the aquatic environment; The voltage control quantity is generated using the air supply pressure parameter and the water depth parameter. The voltage control quantity is used to drive the electromagnetic valve associated with the bottom aeration array, so that the electromagnetic valve outputs a dynamic microbubble refractive grating with the central low-density area and the peripheral high-density area in the vertical space of the water body. Extract the structural evolution period of the dynamic microbubble refractive grating, and generate the discontinuous acoustic phased array driving timing corresponding to the central low-density region based on the structural evolution period; Based on the discontinuous acoustic phased array driven time-series transmission of orthogonal frequency division multiplexing time-domain symbol sequence, the background backscattering Doppler frequency shift characteristics generated by the orthogonal frequency division multiplexing time-domain symbol sequence penetrating the peripheral high-density region are extracted; Compare the background backscattering Doppler frequency shift characteristics with the preset waveguide penetration conditions, and generate a high-level trigger quantity when the comparison result meets the preset waveguide penetration conditions; The power supply to the communication receiving circuit is cut off using the high-level trigger quantity, the surplus power quota is obtained, and the surplus power quota is transferred to the water quality sampling circuit.

2. The intelligent cost optimization method for the entire aquaculture process according to claim 1, characterized in that, The process of generating a voltage control quantity using the air supply pressure parameters and the water depth parameters, and using the voltage control quantity to drive an electromagnetic valve associated with the underwater aeration array, so that the electromagnetic valve outputs a dynamic microbubble refractive grating with the central low-density region and the peripheral high-density region in the vertical space of the water body, includes: Based on the gas supply pressure parameters and the water depth parameters, a partial differential equation of fluid dynamics space is established and solved to output the fluid dynamics distribution matrix. The fluid dynamics distribution matrix is ​​sliced ​​according to the time dimension to generate a pulse width modulation sequence with time interval attributes; The pulse width modulation sequence is converted into the voltage control quantity, and the electromagnetic valve is driven to open and close according to the voltage control quantity in a set sequence, so as to output the dynamic microbubble refractive grating with the central low-density area and the peripheral high-density area in the vertical space of the water body.

3. The intelligent cost optimization method for the entire aquaculture process according to claim 2, characterized in that, The extraction of the structural evolution period of the dynamic microbubble refractive grating includes: A probe signal is emitted to the dynamic microbubble refractive grating; The backscattered sound waves generated after the probe pilot signal is incident on the peripheral high-density area are extracted, and the backscattered sound waves are converted into a discrete digital matrix; The discrete digital matrix is ​​subjected to envelope detection operation to output the spatial gradient distribution matrix of the sound wave reflection intensity; A peak detection algorithm is applied to the spatial gradient distribution matrix to extract the coordinates of the minimum decay values ​​in the spatial gradient distribution matrix. The coordinate point of the minimum attenuation value is set as the center position within the central low-density region, and the value of the center position changing over time is extracted as the structural evolution period.

4. The intelligent cost optimization method for the entire aquaculture process according to claim 3, characterized in that, The step of generating the discontinuous acoustic phased array driving timing corresponding to the central low-density region based on the structural evolution period includes: Extract the spatial coordinates of the center position; Based on the relative geometric position of the spatial coordinate point and the signal transmitting end, perform spatial trigonometric function calculations and output relative angle parameters; The phase delay time parameter of the independent transmitting element in the acoustic wave transmitting array is calculated based on the relative angle parameter. The phase delay time parameter is used to generate the driving timing of the discontinuous acoustic phased array that matches the central low-density region.

5. The intelligent cost optimization method for the entire aquaculture process according to claim 4, characterized in that, The transmitted orthogonal frequency division multiplexing time-domain symbol sequence includes: Collect the digital value of dissolved oxygen concentration output by the water quality sampling circuit; The digital value of dissolved oxygen concentration is mapped to complex constellation points using quadrature amplitude modulation logic. Perform an inverse fast Fourier transform operation on the complex constellation points to generate the orthogonal frequency division multiplexing time-domain symbol sequence; Obtain the hardware system timestamp, and align the continuous transmission time window of the orthogonal frequency division multiplexing time domain symbol sequence with the time period of the central low-density area based on the underlying timestamp.

6. The intelligent cost optimization method for the entire aquaculture process according to claim 5, characterized in that, The extraction of the background backscattering Doppler frequency shift features generated by the orthogonal frequency division multiplexing time-domain symbol sequence penetrating the peripheral high-density region includes: The orthogonal frequency division multiplexing time-domain symbol sequence is converted into a mechanical vibration signal and radiated into the water body according to the discontinuous acoustic phased array driven timing-driven acoustic wave transmitting array. The mechanical vibration signal is received, penetrates the central low-density region, and undergoes fluid interface scattering with the peripheral high-density region, generating a scattered echo; A fast Fourier transform is performed on the scattered echo, and the frequency domain peak value is extracted as the background backscattering Doppler frequency shift feature.

7. The intelligent cost optimization method for the entire aquaculture process according to claim 6, characterized in that, The comparison of the background backscattering Doppler frequency shift characteristics with a preset waveguide penetration condition, and the generation of a high-level trigger signal when the comparison result meets the preset waveguide penetration condition, and the use of the high-level trigger signal to cut off the power supply to the communication receiving circuit, includes: Extract the center frequency of the frequency shift contained in the background backscattering Doppler frequency shift feature; Compare the frequency shift center frequency with the frequency offset extreme values ​​included in the preset waveguide penetration condition; When the frequency shift center frequency reaches the frequency deviation extreme value, the high-level trigger value is output; The high-level trigger signal drives the solid-state switch circuit to disconnect the power supply circuit of the communication receiving circuit, thereby cutting off the power supply to the communication receiving circuit.

8. The intelligent cost optimization method for the entire aquaculture process according to claim 7, characterized in that, The step of acquiring surplus power quotas and transferring the surplus power quotas to the water quality sampling circuit includes: After cutting off the power supply to the communication receiving circuit, the preset response waiting time and the listening operating current of the communication receiving circuit are extracted. Multiply the preset response waiting time by the listening current to output the standby power value; The standby power value is analyzed and calculated using power allocation logic to generate a compensation power supply pulse width that matches the water quality sampling circuit; The compensation power supply pulse width is determined as the surplus power quota, and the energy distribution network is reconstructed at the underlying hardware level to transfer the surplus power quota to the water quality sampling circuit.

9. The intelligent cost optimization method for the entire aquaculture process according to claim 8, characterized in that, After acquiring surplus power quotas and transferring them to the water quality sampling circuit, the process includes: The water quality sampling circuit is driven to increase the sampling frequency by utilizing the transferred surplus power quota, and to collect and output a high-frequency digital quantity of dissolved oxygen concentration. The high-frequency dissolved oxygen concentration digital quantity is encapsulated into a data frame to generate an environmental water quality data packet, which is then buffered and output. Extract the characteristic concentration values ​​from the environmental water quality data package and compare the characteristic concentration values ​​with a preset safe concentration threshold. When the characteristic concentration value reaches the preset safe concentration threshold, a duty cycle decay command is generated, and the opening and closing duty cycle of the solenoid valve is reduced by the duty cycle decay command.

10. An intelligent optimization system for the entire aquaculture process cost, applied to the intelligent optimization method for the entire aquaculture process cost as described in any one of claims 1 to 9, characterized in that, include: The parameter acquisition module is used to acquire the air supply pressure parameters of the underwater aeration array and the water depth parameters of the aquatic environment. The grating generation module is used to generate a voltage control quantity using the air supply pressure parameter and the water depth parameter, and use the voltage control quantity to drive the electromagnetic valve associated with the bottom aeration array, so that the electromagnetic valve outputs a dynamic microbubble refractive grating with the central low-density area and the peripheral high-density area in the vertical space of the water body. The timing generation module is used to extract the structural evolution period of the dynamic microbubble refractive grating and generate a discontinuous acoustic phased array driving timing corresponding to the central low-density region based on the structural evolution period. The feature extraction module is used to extract the background backscattering Doppler frequency shift features generated by the orthogonal frequency division multiplexing time-domain symbol sequence transmitted by the discontinuous acoustic phased array driving the timing transmission of the orthogonal frequency division multiplexing time-domain symbol sequence through the peripheral high-density region. The trigger quantity generation module is used to compare the background backscattering Doppler frequency shift characteristics with the preset waveguide penetration conditions, and generate a high-level trigger quantity when the comparison result meets the preset waveguide penetration conditions. The quota transfer module is used to cut off the power supply to the communication receiving circuit by using the high-level trigger quantity, obtain the surplus power quota, and transfer the surplus power quota to the water quality sampling circuit.

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