Aquatic product survival state monitoring method, device, equipment, medium and product
By analyzing radar technology and signal processing algorithms to monitor aquatic radar wave signals, the problems of low efficiency and insufficient accuracy in monitoring the survival status of aquatic organisms in traditional methods have been solved, achieving efficient and accurate non-contact monitoring.
Patent Information
- Application Number
- CN202511258282.X
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-09-04
- Publication Date
- 2025-12-12
AI Technical Summary
Traditional methods are insufficient for efficient and accurate monitoring of aquatic survival status. Manual observation is inefficient and inaccurate, and contact sensors are prone to causing stress and damage.
Radar technology is used to preprocess the radar wave signals of aquatic organisms. Through Fourier transform and mode decomposition, non-contact monitoring is carried out using indicators such as heart rate, heart rate variability and bubble frequency. Combined with adaptive filtering and constant false alarm rate algorithm to eliminate noise, the survival status of aquatic organisms can be judged in real time.
It enables efficient and accurate monitoring of aquatic survival status, avoids stress responses caused by contact sensors, and improves the accuracy and real-time performance of monitoring.
Smart Images
Figure CN121114995A_ABST
Abstract
Description
Technical Field
[0001] This application relates to the fields of radar technology and sensors, and in particular to a method, apparatus, equipment, medium and product for monitoring the survival status of aquatic organisms. Background Technology
[0002] Detecting the survival of farmed aquatic organisms is crucial because if aquatic organisms die during the farming process, bacteria within their bodies will rapidly multiply and produce harmful substances, causing economic losses to the aquaculture industry. In aquaculture, traditional survival detection methods mainly rely on manual observation or contact sensors, but these methods have significant technical drawbacks and limitations in practical applications:
[0003] Manual observation is inefficient and inaccurate. Because aquatic animals are typically raised in cages, their external characteristics and elusive lifestyles make it difficult to accurately detect subtle vital signs (such as gill movements and limb tremors) with the naked eye. Especially in intensive aquaculture environments, manual inspection is not only time-consuming and labor-intensive, but also prone to misjudgment due to visual fatigue or differences in experience. Furthermore, inspection cannot be conducted around the clock.
[0004] Contact sensors are prone to stress interference. Existing contact sensors (such as electrodes or bioimpedance devices) need to be directly attached to the surface of aquatic organisms. However, aquatic organisms are extremely sensitive to external stimuli, and contact measurements may trigger severe stress responses, leading to distortion of physiological data such as heart rate and movement frequency. In addition, frequent contact may damage the epidermis or appendages, increasing the risk of infection.
[0005] These pain points make it difficult for traditional methods to achieve efficient and accurate survival monitoring, thus hindering the intelligent and large-scale development of aquaculture management. Summary of the Invention
[0006] The purpose of this application is to provide a method, device, equipment, medium and product for monitoring the survival status of aquatic organisms, so as to solve the problem that traditional methods are difficult to achieve efficient and accurate survival monitoring of aquatic organisms.
[0007] To achieve the above objectives, this application provides the following solution:
[0008] Firstly, this application provides a method for monitoring the survival status of aquatic organisms, including:
[0009] The acquired aquatic radar wave signals are preprocessed to determine the preprocessed aquatic radar wave signals.
[0010] The difference signal is determined based on the preprocessed aquatic radar wave signal;
[0011] Determine whether the difference signal meets the judgment condition to obtain a first judgment result;
[0012] If the first judgment result is negative, the preprocessed aquatic radar wave signal is set as a difference signal, and the process returns to the step "determine whether the difference signal meets the judgment condition".
[0013] If the first judgment result is yes, determine the modal components of the difference signal and the residual signal of the difference signal;
[0014] Determine whether the residual signal is monotonic to obtain a second determination result;
[0015] If the second judgment result is yes, the decomposition process ends;
[0016] If the second judgment result is negative, the residual signal is set as the preprocessed radar wave signal, and the process returns to the step "determine the difference signal based on the preprocessed radar wave signal" to obtain multiple mode components.
[0017] Perform Fourier transform on multiple modal components to determine the frequency values of multiple modal components;
[0018] The survival status of aquatic organisms is determined based on the frequency values of multiple modal components.
[0019] In one embodiment, background solid noise is eliminated from the radar wave signal according to a constant false alarm rate algorithm, and the eliminated radar wave signal is determined.
[0020] The eliminated radar wave signal is subjected to LSM adaptive filtering to determine the preprocessed aquatic radar wave signal.
[0021] In one embodiment, the preprocessed aquatic radar wave signal is fitted to determine the fitting curve;
[0022] Data in the fitted curve that are above the preset standard line are used as upper envelope data, and data in the fitted curve that are below the preset standard line are used as lower envelope data.
[0023] Calculate the mean signal of the upper envelope data and the lower envelope data;
[0024] The difference signal is determined using M(t) = P(t) - a(t); where M(t) is the difference signal; P(t) is the preprocessed radar wave signal; and a(t) is the mean signal.
[0025] In one embodiment, the judgment condition is that the absolute value of the difference between the number of extreme points and the number of zero-crossing points of the difference signal is less than or equal to 1, and the mean value formed by the local maxima and local minima in the fitted curve is equal to 0.
[0026] In one embodiment, the survival state includes a living state, a dying state, and a dead state; the modal component is the frequency value of the aquatic animal's heart rate.
[0027] When the heart rate fluctuation of aquatic animals is less than 25% and the heart rate frequency is greater than 0.5 Hz, the aquatic animals are considered to be alive.
[0028] When the heart rate frequency of an aquatic animal is less than 0.5 Hz, it is determined that the aquatic animal is in a near-death state.
[0029] When the heart rate frequency of an aquatic animal is 0, it is determined that the aquatic animal is in a state of death.
[0030] In one embodiment, the residual signal is R i (t)=P(t)-IM i (t); where R i (t) represents the i-th residual signal; P(t) represents the preprocessed radar wave signal; IM i (t) represents the i-th modal component.
[0031] Secondly, this application provides an aquatic survival status monitoring device, comprising:
[0032] The preprocessed signal determination module is used to preprocess the acquired aquatic radar wave signal and determine the preprocessed aquatic radar wave signal.
[0033] The difference signal determination module is used to determine the difference signal based on the preprocessed aquatic radar wave signal.
[0034] The first judgment result determination module is used to determine whether the difference signal meets the judgment condition and obtain the first judgment result;
[0035] The iterative processing module is used to set the preprocessed aquatic radar wave signal as a difference signal and return to the step "determine whether the difference signal meets the judgment condition".
[0036] The residual signal determination module is used to determine the modal components of the difference signal and the residual signal of the difference signal;
[0037] The second judgment result determination module is used to determine whether the residual signal is monotonic and obtain the second judgment result.
[0038] The End Decomposition Process module is used to end the decomposition process.
[0039] The modal component determination module is used to set the residual signal as a preprocessed radar wave signal, return to the step "determine the difference signal according to the preprocessed radar wave signal", and obtain multiple modal components.
[0040] The frequency value determination module is used to perform Fourier transform on multiple modal components to determine the frequency values of multiple modal components;
[0041] The survival status determination module is used to determine the survival status of aquatic organisms based on the frequency values of multiple modal components.
[0042] Thirdly, this application provides a computer device, including: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the steps of the aquatic survival status monitoring method described in any one of the above.
[0043] Fourthly, this application provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of the aquatic survival status monitoring method described above.
[0044] Fifthly, this application provides a computer program product, including a computer program that, when executed by a processor, implements the steps of the aquatic survival status monitoring method described above.
[0045] According to the specific embodiments provided in this application, the following technical effects are disclosed:
[0046] This application provides a method, device, equipment, medium, and product for monitoring the survival status of aquatic organisms. It preprocesses the acquired aquatic radar wave signal to determine the preprocessed signal, thus addressing the issue of contact-based sensors causing severe stress responses that distort physiological data such as heart rate and movement frequency. Based on the preprocessed radar wave signal, a difference signal is determined. The system then determines whether the difference signal meets the judgment conditions, obtaining a first judgment result. If the first judgment result is negative, the preprocessed radar wave signal is set as the difference signal, and the process returns to the step "determine whether the difference signal meets the judgment conditions." If the first judgment result is positive, the modal components and the difference signal are determined. The residual signal is determined; it is judged whether the residual signal is monotonic, and a second judgment result is obtained; if the second judgment result is yes, the decomposition process ends; if the second judgment result is no, the residual signal is set as the preprocessed radar wave signal, and the process returns to the step "determine the difference signal based on the preprocessed radar wave signal" to obtain multiple modal components; Fourier transform is performed on the multiple modal components to determine the frequency values of the multiple modal components; based on the frequency values of the multiple modal components, the survival status of the aquatic products is determined according to the preset frequency value range, and the survival status of the aquatic products is determined in a timely and effective manner. This solves the problem of low efficiency in monitoring the survival status of aquatic products using traditional methods, and realizes efficient and accurate monitoring and determination of the survival status of aquatic products. Attached Figure Description
[0047] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.
[0048] Figure 1 This is a flowchart illustrating a method for monitoring the survival status of aquatic organisms according to an embodiment of this application.
[0049] Figure 2 A schematic diagram of the main hardware components provided in an embodiment of this application;
[0050] Figure 3 This is a schematic diagram of the echo radar signal processing flow provided in an embodiment of this application;
[0051] Figure 4 This is a schematic diagram of a mode decomposition algorithm provided in an embodiment of this application;
[0052] Figure 5 This is a schematic diagram of the structure of a computer device provided in an embodiment of this application. Detailed Implementation
[0053] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.
[0054] To make the above-mentioned objectives, features and advantages of this application more apparent and understandable, the application will be further described in detail below with reference to the accompanying drawings and specific embodiments.
[0055] like Figure 1 As shown in the figure, this application provides a method for monitoring the survival status of aquatic organisms, the specific details of which are as follows.
[0056] S1: Preprocess the acquired aquatic radar wave signal to determine the preprocessed aquatic radar wave signal.
[0057] S2: Determine the difference signal based on the preprocessed aquatic radar wave signal.
[0058] S3: Determine whether the difference signal meets the judgment condition and obtain the first judgment result. If yes, execute S5; otherwise, execute S4.
[0059] S4: Set the preprocessed aquatic radar wave signal as a difference signal and return to the step "determine whether the difference signal meets the judgment condition".
[0060] S5: Determine the modal components of the difference signal and the residual signal of the difference signal.
[0061] S6: Determine whether the residual signal is monotonic and obtain a second determination result. If yes, execute S7; otherwise, execute S8.
[0062] S7: If the second judgment result is yes, end the decomposition process.
[0063] S8: If the second judgment result is negative, set the residual signal as the preprocessed radar wave signal, return to S2, and obtain multiple modal components.
[0064] S9: Perform Fourier transform on multiple modal components to determine the frequency values of multiple modal components.
[0065] S10: Determine the survival status of aquatic organisms based on the frequency values of multiple modal components.
[0066] like Figure 3 As shown, further, in an exemplary embodiment, S1 can be replaced by the following steps.
[0067] S101: Eliminate background solid noise from the radar wave signal according to the constant false alarm rate algorithm, and determine the radar wave signal after elimination.
[0068] S102: Perform LSM adaptive filtering on the eliminated radar wave signal to determine the preprocessed aquatic radar wave signal.
[0069] Furthermore, in an exemplary embodiment, S2 can be replaced by the following steps.
[0070] S201: Fit the preprocessed aquatic radar wave signal to determine the fitting curve.
[0071] S202: The data in the fitted curve that are above the preset standard line are used as the upper envelope data, and the data in the fitted curve that are below the preset standard line are used as the lower envelope data.
[0072] For the preprocessed radar wave signal P(t), upper envelope E is obtained by fitting the upper and lower envelopes respectively. up (t) and lower envelope E lo (t).
[0073] S203: Calculate the mean signal of the upper envelope data and the lower envelope data.
[0074] S204: Use M(t)=P(t)-a(t) to determine the difference signal; where M(t) is the difference signal; P(t) is the preprocessed radar wave signal; and a(t) is the mean signal.
[0075] Determine whether the difference signal M(t) meets the judgment conditions. The judgment conditions are that the absolute value of the difference between the number of extreme points and the number of zero crossings of the signal M(t) is less than or equal to 1, and the mean of the local maxima and local minima formed by the fitted curve is 0. Both conditions must be met simultaneously.
[0076] If the condition is not met, P(t) is set to M(t), and the step "determine whether the difference signal meets the judgment condition" is repeated. If the condition is met, the first modal component IM1(t) = M(t) is obtained.
[0077] The residual signal is Ri(t) = P(t) - IMi(t); where Ri(t) is the i-th residual signal; P(t) is the preprocessed radar wave signal; and IMi(t) is the i-th modal component.
[0078] like Figure 4 As shown, IM1(t), IM2(t), IM3(t), ... can be obtained through mode decomposition algorithm. Fourier transform of these obtained IM1(t), IM2(t), IM3(t), ... yields their frequency values F1, F2, F3, ... . Among the obtained frequencies, those within the range of 0.8-1.2Hz represent the healthy heart rate of aquatic animals. Frequencies greater than 10Hz are considered bubble-producing frequencies. Furthermore, heart rate fluctuations (HRV assessment) are performed on the aquatic animals' heart rates.
[0079] Of the frequencies obtained above, those within the range of 0.8-1.2Hz represent healthy heart rates in aquatic organisms. Frequencies greater than 10Hz are considered bubble-producing frequencies. Heart rate variability (HRV) is also assessed in the aquatic organisms.
[0080] As shown in Table 1, further, in an exemplary embodiment, S10 can be replaced by the following steps.
[0081] S1001: The survival state includes the living state, the dying state, and the dead state; the modal component is the frequency value of the aquatic heart rate.
[0082] S1002: When the heart rate fluctuation of aquatic animals is <25% and the frequency value of the heart rate of aquatic animals is >0.5Hz, the aquatic animals are determined to be alive.
[0083] S1003: When the heart rate frequency of an aquatic animal is <0.5Hz, it is determined that the aquatic animal is in a near-death state.
[0084] S1004: When the heart rate frequency of aquatic organisms is 0, it is determined that the aquatic organisms are in a state of death.
[0085] Table 1. Criteria for Judging the Survival of Crab-like Aquatic Species
[0086]
[0087] This application presents a method for comprehensively determining the survival status of aquatic organisms using three indicators: heart rate, HRV value, and bubble production rate. Because it utilizes ultrasonic radar to detect vital signs such as heart rate, it avoids the influence of contact sensors on the aquatic organisms. Furthermore, the use of vital signs such as heart rate for judgment ensures data reliability.
[0088] This application innovatively employs millimeter-wave radar technology to accurately capture weak vital signs of aquatic organisms in a non-contact manner, effectively solving the technical problem that traditional image detection methods fail when aquatic organisms are stationary.
[0089] Furthermore, this application provides an aquatic survival status monitoring device, the specific modules of which are described below.
[0090] The preprocessed signal determination module is used to preprocess the acquired aquatic radar wave signal and determine the preprocessed aquatic radar wave signal.
[0091] The difference signal determination module is used to determine the difference signal based on the preprocessed aquatic radar wave signal.
[0092] The first judgment result determination module is used to determine whether the difference signal meets the judgment condition and obtain the first judgment result.
[0093] The iterative processing module is used to set the preprocessed aquatic radar wave signal as a difference signal and return to the step "determine whether the difference signal meets the judgment condition".
[0094] The residual signal determination module is used to determine the modal components of the difference signal and the residual signal of the difference signal.
[0095] The second judgment result determination module is used to determine whether the residual signal is monotonic and obtain the second judgment result.
[0096] The End Decomposition Process module is used to end the decomposition process.
[0097] The modal component determination module is used to set the residual signal as a preprocessed radar wave signal, return to the step "determine the difference signal based on the preprocessed radar wave signal", and obtain multiple modal components.
[0098] The frequency value determination module is used to perform Fourier transform on multiple modal components to determine the frequency values of multiple modal components.
[0099] The survival status determination module is used to determine the survival status of aquatic organisms based on the frequency values of multiple modal components.
[0100] This application uses a 77GHz FMCW (Frequency Modulated Continuous Wave) radar as the core sensor, combined with an adaptive signal processing algorithm and a multimodal decision model, to achieve non-contact monitoring of the vital signs of aquatic organisms. The device involved in this application has a high sampling rate, and with the back-end judgment algorithm, it can realize real-time detection of aquatic organism survival.
[0101] like Figure 2 As shown, the main hardware components of this device include:
[0102] Transmitter:
[0103] An FMCW generator produces a linear frequency modulated (LFM) wave with a starting frequency of 77 GHz and a bandwidth of 4 GHz, with a modulation slope of 70 MHz / µs. The transmit power is boosted to 10 dBm by a power amplifier and then transmitted via a millimeter-wave radar antenna.
[0104] Receiver: Receives signals through a millimeter-wave radar antenna and performs hardware signal processing through a mixer and low-pass filter.
[0105] Baseband processing unit:
[0106] ADC sampling: 100kHz sampling rate, 14-bit resolution, capturing intermediate frequency (IF) signals. Signal processing is then performed via baseband.
[0107] The system workflow can be divided into the following three stages:
[0108] Signal acquisition layer: The millimeter-wave radar transmits a broadband linear frequency modulated signal (bandwidth of 4GHz), which penetrates the aquatic organisms and receives the micro-Doppler echo signal caused by their heartbeats.
[0109] Signal processing layer: Extracts heart rate features through variational mode decomposition.
[0110] Decision output layer: Based on heart rate variability (HRV), heart rate, and bubble frequency, determine the survival status of aquatic animals (surviving / dying / dead).
[0111] In one exemplary embodiment, a computer device is provided, which may be a server or a terminal, and its internal structure diagram may be as follows. Figure 5As shown, this computer device includes a processor, memory, input / output (I / O) interfaces, and a communication interface. The processor, memory, and I / O interfaces are connected via a system bus, and the communication interface is also connected to the system bus via the I / O interfaces. The processor provides computational and control capabilities. The memory includes non-volatile storage media and internal memory. The non-volatile storage media stores the operating system, computer programs, and a database. The internal memory provides the environment for the operation of the operating system and computer programs stored in the non-volatile storage media. The database is used for monitoring the survival status of aquatic organisms. The I / O interfaces are used for exchanging information between the processor and external devices. The communication interface is used for communicating with external terminals via a network connection. The computer program is executed by the processor to implement the monitoring of the survival status of aquatic organisms.
[0112] Those skilled in the art will understand that Figure 5 The structure shown is merely a block diagram of a portion of the structure related to the present application and does not constitute a limitation on the computer device to which the present application is applied. Specific computer devices may include more or fewer components than those shown in the figure, or combine certain components, or have different component arrangements.
[0113] In one exemplary embodiment, a computer device is also provided, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the steps in the above-described method embodiments.
[0114] In one exemplary embodiment, a computer-readable storage medium is provided storing a computer program that, when executed by a processor, implements the steps in the above-described method embodiments.
[0115] In one exemplary embodiment, a computer program product is provided, including a computer program that, when executed by a processor, implements the steps in the above-described method embodiments.
[0116] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, data stored, data displayed, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of the relevant data must comply with relevant regulations.
[0117] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium, and when executed, it can include the processes of the embodiments of the above methods. Any references to memory, databases, or other media used in the embodiments provided in this application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM can take many forms, such as Static Random Access Memory (SRAM) or Dynamic Random Access Memory (DRAM).
[0118] The databases involved in the embodiments provided in this application may include at least one type of relational database and non-relational database. Non-relational databases may include, but are not limited to, blockchain-based distributed databases. The processors involved in the embodiments provided in this application may be general-purpose processors, central processing units, graphics processing units, digital signal processors, programmable logic devices, quantum computing-based data processing logic devices, etc., and are not limited to these.
[0119] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.
[0120] This document uses specific examples to illustrate the principles and implementation methods of this application. The descriptions of the above embodiments are only for the purpose of helping to understand the methods and core ideas of this application. Furthermore, those skilled in the art will recognize that, based on the ideas of this application, there will be changes in the specific implementation methods and application scope. Therefore, the content of this specification should not be construed as a limitation of this application.
Claims
1. An aquatic life condition monitoring method, characterized by, The aquatic survival state monitoring method comprises the following steps: The acquired aquatic radar wave signal is preprocessed to determine the preprocessed aquatic radar wave signal; According to the preprocessed aquatic radar wave signal, a difference signal is determined; It is judged whether the difference signal meets the judgment condition to obtain a first judgment result; If the first judgment result is no, the preprocessed aquatic radar wave signal is set as the difference signal, and the step of judging whether the difference signal meets the judgment condition is returned to; If the first judgment result is yes, the modal component of the difference signal and the residual signal of the difference signal are determined; It is judged whether the residual signal is monotonic to obtain a second judgment result; If the second judgment result is yes, the decomposition process is ended; If the second judgment result is no, the residual signal is set as the preprocessed radar wave signal, and the step of determining the difference signal according to the preprocessed radar wave signal is returned to obtain multiple modal components; The multiple modal components are subjected to Fourier transformation to determine the frequency values of the multiple modal components; Based on the frequency values of the multiple modal components, the survival state of the aquatic product is determined.
2. The aquatic life condition monitoring method according to claim 1, wherein The acquired aquatic radar wave signal is preprocessed to determine the preprocessed aquatic radar wave signal, specifically including: The radar wave signal is subjected to background solid noise elimination according to the constant false alarm rate algorithm to determine the eliminated radar wave signal; The eliminated radar wave signal is subjected to LSM adaptive filtering to determine the preprocessed aquatic radar wave signal.
3. The aquatic life condition monitoring method according to claim 1, wherein According to the preprocessed aquatic radar wave signal, a difference signal is determined, specifically including: The preprocessed aquatic radar wave signal is fitted to determine a fitting curve; The data above the preset standard line in the fitting curve is taken as upper envelope data, and the data below the preset standard line in the fitting curve is taken as lower envelope data; The mean value signal of the upper envelope data and the lower envelope data is calculated; The difference signal is determined by M(t)=P(t)-a(t), wherein M(t) is the difference signal, P(t) is the preprocessed radar wave signal, and a(t) is the mean value signal.
4. The aquatic life condition monitoring method according to claim 3, wherein The judgment condition is that the absolute value of the difference between the extreme point and the zero-crossing point of the difference signal is less than or equal to 1, and the mean value formed by the local maximum point and the local minimum point in the fitting curve is equal to 0.
5. The aquatic life condition monitoring method according to claim 1, wherein Based on the frequency values of the multiple modal components, the survival state of the aquatic product is determined, specifically including: The survival state includes survival state, dying state and death state; the modal component is the frequency value of the aquatic heart rate; When the aquatic heart rate fluctuation is less than 25% and the frequency value of the aquatic heart rate is greater than 0.5 Hz, it is determined that the aquatic product is in a survival state; When the frequency value of the aquatic heart rate is less than 0.5 Hz, it is determined that the aquatic product is in a dying state; When the frequency value of the aquatic heart rate is equal to 0, it is determined that the aquatic product is in a death state.
6. The aquatic life condition monitoring method of claim 1, wherein, The residual signal is R i (t) = P(t) - IM i (t); wherein R i (t) is the i-th residual signal; P(t) is the pre-processed radar wave signal; IM i (t) is the i-th modal component.
7. An aquatic life condition monitoring apparatus characterized by comprising: The aquatic survival state monitoring device comprises: A preprocessed signal determination module for preprocessing the acquired aquatic radar wave signal to determine the preprocessed aquatic radar wave signal; A difference signal determination module for determining a difference signal according to the preprocessed aquatic radar wave signal; The first determination result determination module is configured to determine whether the difference signal meets a determination condition to obtain a first determination result. The iteration processing module is configured to set the preprocessed aquatic radar wave signal as a difference signal, and return to the step of determining whether the difference signal meets a determination condition. The residual signal determination module is configured to determine a modal component of the difference signal and a residual signal of the difference signal. The second determination result determination module is configured to determine whether the residual signal is monotonic to obtain a second determination result. The end of the decomposition process module is configured to end the decomposition process. The modal component determination module is configured to set the residual signal as the preprocessed radar wave signal, return to the step of determining the difference signal according to the preprocessed radar wave signal, and obtain a plurality of modal components. The frequency value determination module is configured to perform Fourier transformation on the plurality of modal components to determine frequency values of the plurality of modal components. The survival state determination module is configured to determine the survival state of the aquatic product based on the frequency values of the plurality of modal components.
8. A computer device comprising: The memory, the processor, and the computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the aquatic survival state monitoring method of any one of claims 1-6.
9. A computer readable storage medium having stored thereon a computer program, characterized in that, The computer program is executed by the processor to implement the aquatic survival state monitoring method of any one of claims 1-6.
10. A computer program product comprising a computer program, characterized in that, The computer program is executed by the processor to implement the aquatic survival state monitoring method of any one of claims 1-6.