CN117337796A - Intelligent accurate feeding method for floating materials in freshwater fish culture pond - Google Patents
Intelligent accurate feeding method for floating materials in freshwater fish culture pond Download PDFInfo
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- 241000251468 Actinopterygii Species 0.000 title claims abstract description 88
- 239000000463 material Substances 0.000 title claims abstract description 67
- 239000013505 freshwater Substances 0.000 title claims abstract description 47
- 238000000034 method Methods 0.000 title claims abstract description 39
- XLYOFNOQVPJJNP-UHFFFAOYSA-N water Substances O XLYOFNOQVPJJNP-UHFFFAOYSA-N 0.000 claims abstract description 57
- 238000012544 monitoring process Methods 0.000 claims abstract description 14
- 238000005266 casting Methods 0.000 claims description 13
- 239000004677 Nylon Substances 0.000 claims description 8
- 229920001778 nylon Polymers 0.000 claims description 8
- 230000000694 effects Effects 0.000 claims description 7
- 230000002265 prevention Effects 0.000 claims description 5
- 208000034699 Vitreous floaters Diseases 0.000 claims 1
- 230000009467 reduction Effects 0.000 abstract description 4
- 238000009395 breeding Methods 0.000 description 17
- 230000001488 breeding effect Effects 0.000 description 17
- 238000009360 aquaculture Methods 0.000 description 8
- 244000144974 aquaculture Species 0.000 description 8
- 238000005516 engineering process Methods 0.000 description 8
- 230000007613 environmental effect Effects 0.000 description 7
- 241001465754 Metazoa Species 0.000 description 6
- 230000004634 feeding behavior Effects 0.000 description 5
- 230000008569 process Effects 0.000 description 5
- 230000009286 beneficial effect Effects 0.000 description 4
- 238000011160 research Methods 0.000 description 4
- 230000008859 change Effects 0.000 description 3
- 230000004048 modification Effects 0.000 description 3
- 238000012986 modification Methods 0.000 description 3
- 235000016709 nutrition Nutrition 0.000 description 3
- 230000035764 nutrition Effects 0.000 description 3
- 230000006399 behavior Effects 0.000 description 2
- 238000010586 diagram Methods 0.000 description 2
- 230000006978 adaptation Effects 0.000 description 1
- 230000007547 defect Effects 0.000 description 1
- 230000037406 food intake Effects 0.000 description 1
- 238000009434 installation Methods 0.000 description 1
- 238000012545 processing Methods 0.000 description 1
Classifications
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- A—HUMAN NECESSITIES
- A01—AGRICULTURE; FORESTRY; ANIMAL HUSBANDRY; HUNTING; TRAPPING; FISHING
- A01K—ANIMAL HUSBANDRY; CARE OF BIRDS, FISHES, INSECTS; FISHING; REARING OR BREEDING ANIMALS, NOT OTHERWISE PROVIDED FOR; NEW BREEDS OF ANIMALS
- A01K61/00—Culture of aquatic animals
- A01K61/80—Feeding devices
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02A—TECHNOLOGIES FOR ADAPTATION TO CLIMATE CHANGE
- Y02A40/00—Adaptation technologies in agriculture, forestry, livestock or agroalimentary production
- Y02A40/80—Adaptation technologies in agriculture, forestry, livestock or agroalimentary production in fisheries management
- Y02A40/81—Aquaculture, e.g. of fish
Abstract
The invention relates to the technical field of freshwater fish culture, in particular to an intelligent accurate feeding method for buoyancy materials of a freshwater fish culture pond, which comprises a feeding machine and a freshwater fish culture pond, wherein the feeding machine is arranged on a pond dike at one side of the freshwater fish culture pond, a buoyancy material enclosure frame is arranged on the water surface of the feeding machine, a high-definition camera is arranged above the buoyancy material enclosure frame and is connected with the input end of a digital signal processor, and an underwater acoustic sensor is arranged below the buoyancy material enclosure frame; piezoelectric sensors are arranged on the front side and the rear side of the bottom of the buoyancy material enclosing frame, and the output ends of the piezoelectric sensors are connected with the input ends of the digital signal processor; according to the invention, the underwater acoustic sensor is used for acquiring the intake desire of the fish shoal, the piezoelectric sensor is used for acquiring the water temperature fluctuation intensity, the high-definition camera is used for reading the residual bait quantity, the feeding model is less interfered, noise reduction treatment is not needed, and the accuracy is high; the decision can realize on-line real-time monitoring and remote regulation and control, and is convenient for management.
Description
Technical Field
The invention relates to the technical field of freshwater fish culture, in particular to an intelligent accurate feeding method for buoyancy materials in a freshwater fish culture pond.
Background
The feed is the most important cost in the aquaculture process and generally accounts for 40% -80% of the total aquaculture cost. Along with the gradual change of the feeding mode of the feed from manual feeding to automatic feeding, in the past 30 years, researchers focus on the deep research based on feeding behaviors (including growth parameters, distribution states, activity indexes, water surface fluctuation change characteristics caused by feeding and the like) and non-feeding behaviors (including residual feeds, feeding audios, environmental parameters, bioenergy and the like) of a breeding object, except for researching a self-required feeding-based accurate feeding technical method, monitor, analyze and process each parameter by using technical means such as computer vision, optics, acoustics and various sensors, and quantize feeding intensity by an algorithm model so as to realize accurate feeding.
However, the above methods and techniques suffer from the following disadvantages:
the complexity of the dynamic superposition culture mode of the variety of the culture in the freshwater culture pond and the nutrition requirement in the growing period leads to huge workload in the early stage of the feeding decision algorithm model based on the growth of fishes and the energy requirement; the decision model and the parameters thereof are difficult to quickly determine according to different breeding objects, breeding environments and breeding modes, so that the universality is poor and the accuracy is low;
the environmental complexity of the traditional pond culture mode determines that the feeding decision model constructed according to only a single parameter is low in accuracy and poor in practicability, so that an intelligent accurate feeding method for the floating materials of the freshwater fish culture pond is provided for the problems.
Disclosure of Invention
The invention aims to provide an intelligent accurate feeding method for floating materials in a freshwater fish culture pond, which aims to solve the problems in the background art.
In order to achieve the above purpose, the present invention provides the following technical solutions:
as an alternative scheme of the intelligent accurate feeding method for the floating materials of the freshwater fish culture pond, the invention comprises the following steps: an intelligent accurate feeding method for floating materials of a freshwater fish culture pond comprises a feeding machine, a floating material surrounding frame, an underwater acoustic sensor, a piezoelectric sensor, a high-definition camera, a digital signal processor, a display screen and the freshwater fish culture pond,
the bait feeder is arranged on a pond dike at one side of the freshwater fish culture pond, and is controlled by an instruction sent by the digital signal processor to execute feeding or stop feeding functions;
the bait casting machine is characterized in that a buoyancy material surrounding frame is arranged on the water surface of the bait casting machine, a high-definition camera is arranged above the buoyancy material surrounding frame, and the high-definition camera is connected with the input end of the digital signal processor and is used for monitoring the condition of the residual bait in the buoyancy material surrounding frame on line in real time;
an underwater acoustic sensor is arranged below the buoyancy material surrounding frame and is arranged at the bottom of the freshwater fish culture pond, and the output end of the underwater acoustic sensor and the digital signal processor are used for monitoring the behavior of the shoal of fish on line in real time;
piezoelectric sensors are arranged on the front side and the rear side of the bottom of the buoyancy material surrounding frame, and the output ends of the piezoelectric sensors are connected with the input end of the digital signal processor and are used for monitoring the fluctuation intensity of water waves on line in real time;
the output end of the digital signal processor is connected with the bait casting machine and the display screen at the same time.
The feed is the most important cost in the aquaculture process and generally accounts for 40% -80% of the total aquaculture cost. Along with the feed feeding mode, manual feeding is gradually changed into automatic feeding, in the last 30 years, except for researching a precision feeding technical method based on self-needed feeding, researchers focus on developing deep research based on feeding behaviors and non-feeding behaviors of a breeding object, monitor, analyze and process various parameters by using technical means such as computer vision, optics, acoustics and various sensors, and quantize feeding strength through an algorithm model so as to realize precision feeding.
However, the above methods and techniques suffer from the following disadvantages: the method and the technology are mainly applied to laboratories, pond circulating water, industrialization and net cage culture modes with relatively stable water environment, and are not applicable to traditional pond culture modes which are more dynamic, open, complex and uncontrollable; especially, the feeding decision based on the computer vision technology has lower decision accuracy due to the problem of low transparency of the pond water body and uncertainty of environmental parameters; the feeding decision model constructed only according to the engineering modeling theory ignores the physiological and ecological characteristics of the fish, and is essentially unsuitable for the freshwater aquaculture industry; the complexity of the dynamic superposition culture mode of the variety of the culture in the freshwater culture pond and the nutrition requirement in the growing period leads to huge workload in the early stage of the feeding decision algorithm model based on the growth of fishes and the energy requirement; the decision model and the parameters thereof are difficult to quickly determine according to different breeding objects, breeding environments and breeding modes, so that the universality is poor and the accuracy is low; the environmental complexity of the traditional pond culture mode determines that the feeding decision model constructed only according to a single parameter has low accuracy and poor practicability; when the device is used, the underwater acoustic sensor is used for acquiring the ingestion desire of the fish shoal, the piezoelectric sensor is used for acquiring the water temperature fluctuation intensity, the high-definition camera is used for reading the residual bait, the feeding model is less interfered, noise reduction treatment is not needed, and the accuracy is high; the decision can realize on-line real-time monitoring and remote regulation and control, so that the management is convenient; the method is suitable for a traditional freshwater fish pond culture mode which is dynamic, open, complex and uncontrollable; the freshwater fish culture pond fed with buoyancy materials is applicable and has high universality without being limited by the culture variety and culture environment of the pond; the precise feeding technology is based on the overall feeding desire and the fluctuation intensity of water waves of the fish shoal, the water surface residual bait data is assisted, the feeding model integrates multiple parameters of a breeding animal end, a breeding environment end and a feed end, and compared with a feeding decision model constructed by single parameters, the decision reliability is higher; the invention can scientifically and effectively reflect the actual feed demand of the fish shoal, is beneficial to constructing a high-efficiency healthy cultivation mode, reduces cultivation cost, promotes animal welfare and reduces CNP emission at the feed end.
As an alternative scheme of the intelligent accurate feeding method for the floating materials of the freshwater fish culture pond, the invention comprises the following steps: the floating material enclosure frame comprises a bottom frame, side frames and bird prevention nets, wherein the side frames are arranged on the periphery of the upper side of the bottom frame, and the bird prevention nets are arranged on the upper side of the side frames.
As an alternative scheme of the intelligent accurate feeding method for the floating materials of the freshwater fish culture pond, the invention comprises the following steps: nylon ropes are connected to four corners of the side frames, and the side frames are fixed on the water surface of the pond through the nylon ropes.
As an alternative scheme of the intelligent accurate feeding method for the floating materials of the freshwater fish culture pond, the invention comprises the following steps: the aperture of the bird preventing net is 3cm.
As an alternative scheme of the intelligent accurate feeding method for the floating materials of the freshwater fish culture pond, the invention comprises the following steps: the side frames adopt 60-mesh dense nets.
And when throwing the material, the buoyancy material can be thrown through the bait throwing machine, can ensure through the aperture of the bird prevention net that sets up that the buoyancy material normally falls to the bird prevention net can avoid some birds to rob the material, and the side frame is connected through the nylon rope and is installed, and the mesh has been seted up on the side frame surface that sets up simultaneously, is used for the normal flow of water.
As an alternative scheme of the intelligent accurate feeding method for the floating materials of the freshwater fish culture pond, the invention comprises the following steps: the method comprises the following steps:
step one: daily basic data acquisition: collecting data of the active intensity, the fluctuation intensity of water waves and the residual bait quantity in the surrounding material frame of the floating material below the surrounding material frame in the feeding period and the non-feeding period, and acquiring the active intensity, the fluctuation intensity of water waves and the residual bait data of the fish shoal and calculating a mean value;
step two: the first step is specifically divided into the following steps:
a: acquiring data F1-Fn and W1-Wn of the active intensity and the water wave fluctuation intensity of the fish shoal by an underwater acoustic sensor and a piezoelectric sensor in real time, wherein the acquisition time interval is 0.8-1.5 seconds, and the time is T1 and T2;
b: the fish shoal active intensity delta F1-delta Fn and the water wave fluctuation intensity delta W1-delta Wn are obtained through the formulas delta Fn= FnT2-FnT1 and delta Wn= WnT2-WnT 1;
c: calculating average value of active intensity of fish shoalAnd mean value of fluctuation intensity of water wave->
Step three: after the bait casting machine starts feeding, the digital signal processor firstly analyzes the information transmitted by the received underwater acoustic sensor and the piezoelectric sensor, and monitors the changes of the active intensity and the water wave fluctuation intensity of the fish shoal in real time through the underwater acoustic sensor and the piezoelectric sensor;
when the active intensity value of the fish shoal is more than 3 times of the average daily intensity value and the fluctuation intensity of the water wave is more than 1.5 times of the average daily intensity value, continuously feeding the fish shoal;
when the active intensity value of the fish shoal is more than 1.5 times of the average daily intensity value and the fluctuation intensity of the water wave is more than 1 time of the average daily intensity value, the feeding amount is halved;
when the average daily intensity value is less than or equal to the average daily intensity value of the fish shoal, is more than or equal to 1 time, and the average daily intensity value is less than or equal to the average daily intensity value of the water ripple fluctuation intensity is less than or equal to 0.5 time, the digital signal processor automatically acquires the data monitored by the high-definition camera in real time, the feeding is controlled by the underwater acoustic sensor and the piezoelectric sensor to be switched to the feeding controlled by the high-definition camera, and when the quantity of residual baits after feeding for 6 seconds is greater than 1/7 of the single feeding quantity, the digital signal processor sends a command for stopping feeding.
Compared with the prior art, the invention has the beneficial effects that:
the invention is suitable for a traditional dynamic, open, complex and uncontrollable freshwater fish pond culture (feeding buoyancy material) mode;
the method is not limited by the culture variety and the culture environment of the pond, is applicable to freshwater fish culture ponds fed with buoyancy materials, and has high universality;
according to the invention, the underwater acoustic sensor is used for acquiring the intake desire of the fish shoal, the piezoelectric sensor is used for acquiring the water temperature fluctuation intensity, the high-definition camera is used for reading the residual bait quantity, the feeding model is less interfered, noise reduction treatment is not needed, and the accuracy is high; the decision can realize on-line real-time monitoring and remote regulation and control, so that the management is convenient;
the precise feeding technology is based on the overall feeding desire and the fluctuation intensity of water waves of the fish shoal, the water surface residual bait data is assisted, the feeding model integrates multiple parameters of a breeding animal end, a breeding environment end and a feed end, and compared with a feeding decision model constructed by single parameters, the decision reliability is higher;
the invention can scientifically and effectively reflect the actual feed demand of the fish shoal, is beneficial to constructing a high-efficiency healthy cultivation mode, reduces cultivation cost, promotes animal welfare and reduces CNP emission at the feed end.
Drawings
FIG. 1 is a schematic structural diagram of an intelligent accurate feeding method for floating materials in a freshwater fish culture pond;
fig. 2 is a schematic diagram of a buoyancy material enclosure frame structure of an intelligent accurate feeding method for buoyancy materials of a freshwater fish culture pond.
In the figure: 1. a bait throwing machine; 2. a buoyancy material surrounding frame; 201. a bottom frame; 202. a side frame; 203. an anti-bird net; 3. an underwater acoustic sensor; 4. a piezoelectric sensor; 5. a high definition camera; 6. a digital signal processor; 7. a display screen; 8. freshwater fish culture pond.
Detailed Description
Example 1:
referring to fig. 1, the present invention provides a technical solution:
an intelligent accurate feeding method for floating materials in a freshwater fish culture pond comprises a bait casting machine 1, a floating material surrounding frame 2, an underwater acoustic sensor 3, a piezoelectric sensor 4, a high-definition camera 5, a digital signal processor 6, a display screen 7 and a freshwater fish culture pond 8,
the bait feeder 1 is arranged on a dike on one side of the freshwater fish culture pond 8, and the bait feeder 1 is controlled by an instruction sent by the digital signal processor 6 to execute feeding or stop feeding functions;
the bait casting machine 1 is provided with a buoyancy material surrounding frame 2 on the water surface, a high-definition camera 5 is arranged above the buoyancy material surrounding frame 2, and the high-definition camera 5 is connected with the input end of a digital signal processor 6 and is used for monitoring the condition of the residual bait in the buoyancy material surrounding frame 2 on line in real time;
an underwater acoustic sensor 3 is arranged below the buoyancy material enclosing frame 2, the underwater acoustic sensor 3 is arranged at the bottom of the freshwater fish culture pond 8, and the output end of the underwater acoustic sensor 3 and the digital signal processor 6 are used for monitoring the behavior of the shoal in real time on line;
the piezoelectric sensors 4 are arranged on the front side and the rear side of the bottom of the buoyancy material enclosing frame 2, and the output ends of the piezoelectric sensors 4 are connected with the input end of the digital signal processor 6 and are used for monitoring the fluctuation intensity of water waves on line in real time;
the output end of the digital signal processor 6 is connected with the bait casting machine 1 and the display screen 7.
The method comprises the following steps:
step one: daily basic data acquisition: collecting data of the activity intensity, the fluctuation intensity of water waves of the shoal of fish below the floating material enclosure frame 2 and the residual bait quantity in the enclosure frame during feeding and during non-feeding, and acquiring the activity intensity, the fluctuation intensity of water waves and the residual bait data of the shoal of fish and calculating a mean value;
step two: the first step is specifically divided into the following steps:
a: acquiring data F1-Fn and W1-Wn of the active intensity and the water wave fluctuation intensity of the fish shoal by an underwater acoustic sensor and a piezoelectric sensor in real time, wherein the acquisition time interval is 0.8-1.5 seconds, and the time is T1 and T2;
b: the fish shoal active intensity delta F1-delta Fn and the water wave fluctuation intensity delta W1-delta Wn are obtained through the formulas delta Fn= FnT2-FnT1 and delta Wn= WnT2-WnT 1;
c: calculating average value of active intensity of fish shoalAnd mean value of fluctuation intensity of water wave->
Step three: after the bait casting machine starts feeding work, the digital signal processor 6 firstly analyzes the information transmitted by the received underwater acoustic sensor 3 and the piezoelectric sensor 4, and monitors the changes of the activity intensity and the water wave fluctuation intensity of the fish shoal in real time through the underwater acoustic sensor 3 and the piezoelectric sensor 4;
when the active intensity value of the fish shoal is more than 3 times of the average daily intensity value and the fluctuation intensity of the water wave is more than 1.5 times of the average daily intensity value, continuously feeding the fish shoal;
when the active intensity value of the fish shoal is more than 1.5 times of the average daily intensity value and the fluctuation intensity of the water wave is more than 1 time of the average daily intensity value, the feeding amount is halved;
when the average daily intensity value is less than or equal to the average daily intensity value of the fish shoal, is more than or equal to 1 time, and the average daily intensity value is less than or equal to the average daily intensity value of the water ripple fluctuation intensity is less than or equal to 0.5 time, the digital signal processor automatically acquires the data monitored by the high-definition camera in real time, the feeding is controlled by the underwater acoustic sensor 3 and the piezoelectric sensor 4 to be switched to the feeding controlled by the high-definition camera 5, and when the quantity of residual baits after feeding for 6 seconds is greater than 1/7 single feeding quantity, the digital signal processor 6 sends a command for stopping feeding.
The feed is the most important cost in the aquaculture process, and generally accounts for 40% -80% of the total aquaculture cost, as the feeding mode is gradually changed from manual feeding to automatic feeding, in the last 30 years, researchers focus on the research of accurate feeding technical methods based on self-required feeding, including growth parameters, distribution states, activity indexes, water surface fluctuation change characteristics caused by feeding and the like, non-feeding behaviors including residual feeds, feeding audios, environmental parameters, bioenergy and the like, and carry out intensive research on monitoring, analyzing and processing the parameters by using technical means such as computer vision, optics, acoustics and various sensors, and quantifying feeding strength through an algorithm model so as to realize accurate feeding, but the method and the technology have the following defects: the method and the technology are mainly applied to laboratories, pond circulating water, industrialization and net cage culture modes with relatively stable water environment, and are not applicable to traditional pond culture modes which are more dynamic, open, complex and uncontrollable; especially, the feeding decision based on the computer vision technology has lower decision accuracy due to the problem of low transparency of the pond water body and uncertainty of environmental parameters; the feeding decision model constructed only according to the engineering modeling theory ignores the physiological and ecological characteristics of the fish, and is essentially unsuitable for the freshwater aquaculture industry; the complexity of the dynamic superposition culture mode of the variety of the culture in the freshwater culture pond and the nutrition requirement in the growing period leads to huge workload in the early stage of the feeding decision algorithm model based on the growth of fishes and the energy requirement; the decision model and the parameters thereof are difficult to quickly determine according to different breeding objects, breeding environments and breeding modes, so that the universality is poor and the accuracy is low; the environmental complexity of the traditional pond culture mode determines that the feeding decision model constructed only according to a single parameter has low accuracy and poor practicability; when the device is used, the underwater acoustic sensor 3 is used for acquiring the intake desire of the fish shoal, the piezoelectric sensor 4 is used for acquiring the water temperature fluctuation intensity, the high-definition camera 5 is used for reading the residual bait quantity, the feeding model is less interfered, noise reduction treatment is not needed, and the accuracy is high; the decision can realize on-line real-time monitoring and remote regulation and control, so that the management is convenient; the method is suitable for a more dynamic, open, complex and uncontrollable feeding buoyancy model of the traditional freshwater fish pond culture; the freshwater fish culture pond fed with buoyancy materials is applicable and has high universality without being limited by the culture variety and culture environment of the pond; the precise feeding technology is based on the overall feeding desire and the fluctuation intensity of water waves of the fish shoal, the water surface residual bait data is assisted, the feeding model integrates multiple parameters of a breeding animal end, a breeding environment end and a feed end, and compared with a feeding decision model constructed by single parameters, the decision reliability is higher; the invention can scientifically and effectively reflect the actual feed demand of the fish shoal, is beneficial to constructing a high-efficiency healthy cultivation mode, reduces cultivation cost, promotes animal welfare and reduces CNP emission at the feed end.
Example 2
In this embodiment, referring to fig. 2, the floating material enclosure frame 2 includes a bottom frame 201, side frames 202 and a bird preventing net 203, the side frames 202 are installed around the top of the bottom frame 201, and the bird preventing net 203 is installed above the side frames 202.
Nylon ropes are connected to four corners of the side frames 202, and the side frames 202 are fixed to the pond water surface by the nylon ropes.
The aperture of the bird preventing net 203 is 3cm.
The side frame 202 adopts a 60-mesh dense net.
And when throwing the material, buoyancy material can be thrown through throwing bait machine 1, can ensure through the aperture of preventing bird net 203 that sets up that buoyancy material normally falls to prevent bird net 203 can avoid some birds to rob the material, and side frame 202 connects the installation through the nylon rope, and the mesh has been seted up on the side frame 202 surface that sets up simultaneously for the normal flow of water.
The principles and embodiments of the present invention have been described herein with reference to specific examples, the description of which is intended only to facilitate an understanding of the method of the present invention and its core ideas. The foregoing is merely illustrative of the preferred embodiments of this invention, and it is noted that there is objectively no limit to the specific structure disclosed herein, since numerous modifications, adaptations and variations can be made by those skilled in the art without departing from the principles of the invention, and the above-described features can be combined in any suitable manner; such modifications, variations and combinations, or the direct application of the inventive concepts and aspects to other applications without modification, are contemplated as falling within the scope of the present invention.
Claims (6)
1. Accurate feeding system of intelligence to freshwater fish culture pond buoyancy material, its characterized in that:
comprises a bait casting machine (1), a buoyancy material enclosing frame (2), an underwater acoustic sensor (3), a piezoelectric sensor (4), a high-definition camera (5), a digital signal processor (6), a display screen (7) and a freshwater fish culture pond (8),
the bait feeder (1) is arranged on a dike on one side of the freshwater fish culture pond (8), and the bait feeder (1) is controlled by a command sent by the digital signal processor (6) to execute feeding or stop feeding functions;
the bait casting machine is characterized in that a buoyancy material surrounding frame (2) is arranged on the water surface of the bait casting machine (1), a high-definition camera (5) is arranged above the buoyancy material surrounding frame (2), and the high-definition camera (5) is connected with the input end of a digital signal processor (6) and is used for monitoring the condition of residual bait in the buoyancy material surrounding frame (2) on line in real time;
an underwater acoustic sensor (3) is arranged below the buoyancy material enclosing frame (2), the underwater acoustic sensor (3) is arranged at the bottom of the freshwater fish culture pond (8), and the output end of the underwater acoustic sensor (3) and a digital signal processor (6) are used for monitoring the behavior of the fish shoal on line in real time;
piezoelectric sensors (4) are arranged on the front side and the rear side of the bottom of the buoyancy material enclosing frame (2), and the output end of each piezoelectric sensor (4) is connected with the input end of the digital signal processor (6) and used for monitoring the fluctuation intensity of water waves on line in real time;
the output end of the digital signal processor (6) is connected with the bait casting machine (1) and the display screen (7) at the same time.
2. The intelligent accurate feeding system for freshwater fish culture pond floating materials according to claim 1, wherein: the floating material enclosure frame (2) comprises a bottom frame (201), side frames (202) and an anti-bird net (203), wherein the side frames (202) are arranged on the periphery of the upper portion of the bottom frame (201), and the anti-bird net (203) is arranged on the upper portion of the side frames (202).
3. The intelligent accurate feeding system for freshwater fish culture pond floating materials according to claim 2, wherein: nylon ropes are connected to four corners of the side frames (202), and the side frames (202) are fixed on the water surface of the pond through the nylon ropes.
4. The intelligent accurate feeding system for freshwater fish culture pond floating materials according to claim 2, wherein: the aperture of the bird prevention net (203) is 3cm.
5. The intelligent accurate feeding system for freshwater fish culture pond floating materials according to claim 2, wherein: the side frames (202) are of 60-mesh dense net.
6. An intelligent accurate feeding method for freshwater fish culture pond floaters according to any of the claims 1-5, characterized by:
the method comprises the following steps:
step one: daily basic data acquisition: collecting data of the activity intensity, the fluctuation intensity of water waves of the shoal of fish and the residual bait quantity in the surrounding material frame below the floating material surrounding material frame (2) in the feeding period and the non-feeding period, and acquiring the activity intensity, the fluctuation intensity of water waves and the residual bait data of the shoal of fish and calculating a mean value;
step two: the first step is specifically divided into the following steps:
a: acquiring data F1-Fn and W1-Wn of the active intensity and the water wave fluctuation intensity of the fish shoal by an underwater acoustic sensor and a piezoelectric sensor in real time, wherein the acquisition time interval is 0.8-1.5 seconds, and the time is T1 and T2;
b: the fish shoal active intensity delta F1-delta Fn and the water wave fluctuation intensity delta W1-delta Wn are obtained through the formulas delta Fn= FnT2-FnT1 and delta Wn= WnT2-WnT 1;
c: calculating average value of active intensity of fish shoalAnd mean value of fluctuation intensity of water wave->
Step three: after the bait casting machine starts feeding, the digital signal processor (6) firstly analyzes the information transmitted by the received underwater acoustic sensor (3) and the piezoelectric sensor (4), and monitors the changes of the active intensity and the water wave fluctuation intensity of the fish shoal in real time through the underwater acoustic sensor (3) and the piezoelectric sensor (4);
when the active intensity value of the fish shoal is more than 3 times of the average daily intensity value and the fluctuation intensity of the water wave is more than 1.5 times of the average daily intensity value, continuously feeding the fish shoal;
when the active intensity value of the fish shoal is more than 1.5 times of the average daily intensity value and the fluctuation intensity of the water wave is more than 1 time of the average daily intensity value, the feeding amount is halved;
when the average daily intensity value is less than or equal to 1 time of the average daily intensity value of the fish shoal, and the average daily intensity value is less than or equal to 0.5 time of the average daily intensity value of the water ripple fluctuation, the digital signal processor automatically acquires the data monitored by the high-definition camera in real time, the feeding is controlled by the underwater acoustic sensor (3) and the piezoelectric sensor (4) to be switched to the feeding controlled by the high-definition camera (5), and when the quantity of residual baits after feeding for 6 seconds is greater than 1/7 of the single feeding quantity, the digital signal processor (6) sends out a command for stopping feeding.
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| JPH10313730A (en) * | 1997-05-15 | 1998-12-02 | Hitachi Ltd | Automatically feeding device for aquatic living thing |
| CN109717120A (en) * | 2019-03-07 | 2019-05-07 | 河南牧业经济学院 | A kind of fish culture monitoring feeding system and method based on Internet of Things |
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| CN111903571A (en) * | 2020-09-10 | 2020-11-10 | 宁波大学科学技术学院 | Fish culture feeding method based on water body flow field characteristics |
| CN113349111A (en) * | 2021-05-25 | 2021-09-07 | 中国农业大学 | Dynamic feeding method, system and storage medium for aquaculture |
| CN114847209A (en) * | 2022-04-14 | 2022-08-05 | 华中农业大学 | Intelligent fish feeding method and system based on multi-factor comprehensive control |
| CN115202269A (en) * | 2022-08-18 | 2022-10-18 | 江苏大学 | Aquaculture feeding intelligent control system and method thereof |
| CN116541672A (en) * | 2023-04-20 | 2023-08-04 | 华中农业大学 | Fish culture feeding amount decision method based on acoustic information and water surface fluctuation information |
| CN116778309A (en) * | 2022-10-24 | 2023-09-19 | 中国船舶集团有限公司第七一一研究所 | Residual bait monitoring method, device, system and storage medium |
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| CN209546614U (en) * | 2019-02-21 | 2019-10-29 | 山东景明海洋科技有限公司 | A kind of Pelteobagrus fulvidraco pond culture buoyancy feed table |
| CN109717120A (en) * | 2019-03-07 | 2019-05-07 | 河南牧业经济学院 | A kind of fish culture monitoring feeding system and method based on Internet of Things |
| CN111903571A (en) * | 2020-09-10 | 2020-11-10 | 宁波大学科学技术学院 | Fish culture feeding method based on water body flow field characteristics |
| CN113349111A (en) * | 2021-05-25 | 2021-09-07 | 中国农业大学 | Dynamic feeding method, system and storage medium for aquaculture |
| CN114847209A (en) * | 2022-04-14 | 2022-08-05 | 华中农业大学 | Intelligent fish feeding method and system based on multi-factor comprehensive control |
| CN115202269A (en) * | 2022-08-18 | 2022-10-18 | 江苏大学 | Aquaculture feeding intelligent control system and method thereof |
| CN116778309A (en) * | 2022-10-24 | 2023-09-19 | 中国船舶集团有限公司第七一一研究所 | Residual bait monitoring method, device, system and storage medium |
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