CN208188883U - A kind of long-range aquaculture system mass monitoring system - Google Patents
A kind of long-range aquaculture system mass monitoring system Download PDFInfo
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- CN208188883U CN208188883U CN201820405752.XU CN201820405752U CN208188883U CN 208188883 U CN208188883 U CN 208188883U CN 201820405752 U CN201820405752 U CN 201820405752U CN 208188883 U CN208188883 U CN 208188883U
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Abstract
The utility model discloses a kind of long-range aquaculture system mass monitoring systems, it include: acquisition device, remote terminal, the remote terminal is equipped with: neural network module, display module, the neural network module is connect with the acquisition device by internet, the acquisition device is used to acquire the temperature of breeding water body, dissolved oxygen, pH value parameter, the neural network module is used for the temperature of breeding water body, dissolved oxygen, pH value parameter is as learning data, study obtains breeding water body quality category assessment result, the display module is for showing the assessment result.Using neural network module intelligence, breeding water body quality category assessment result is obtained in the parameter using acquisition device acquisition, and show the assessment result by display module, facilitate the quality condition for recognizing current cultivation water body of manager promptly and accurately.The system can be used in aquaculture operation.
Description
Technical field
The utility model relates to technical field of aquaculture, in particular to a kind of long-range aquaculture system quality-monitoring
System.
Background technique
Aquaculture automation and intelligence are one of the developing direction of culture fishery scale, existing aquaculture
Water quality monitoring system generally comprises acquisition device, remote terminal, and acquisition device is used to acquire the parameter of water quality, and data are sent
To remote terminal, then manager analyzes collected parameter by remote terminal, so that water quality situation is obtained, it is convenient
Manager's management.
But people has subjectivity, relies on manpower analysis merely, is difficult judging to change of water quality accurately and timely, from
And cause the loss in aquaculture.
Utility model content
The technical issues of the utility model solves is: existing aquaculture water quality monitoring system is not easy accurate judgement and supports
Grow the quality condition of water body.
The solution that the utility model solves its technical problem is: a kind of long-range aquaculture system quality-monitoring system
System, comprising: acquisition device, remote terminal, the remote terminal are equipped with: neural network module, display module, the neural network
Module is connect with the acquisition device by internet, and the acquisition device is used to acquire temperature, the dissolved oxygen, PH of breeding water body
Value parameter, the neural network module are used to learn using the temperature of breeding water body, dissolved oxygen, pH value parameter as learning data
The assessment result of breeding water body quality category is obtained, the display module is for showing the assessment result.
Further, the acquisition device includes: temperature sensor, dissolved oxygen sensor, pH value sensor, first, second,
Third conditioning circuit, single-chip microcontroller, wireless module, the single-chip microcontroller are connect with wireless module by serial ports, the temperature sensor,
Dissolved oxygen sensor, pH value sensor pass through the first, second, third conditioning circuit respectively and connect with single-chip microcontroller.
Further, first conditioning circuit includes: rectifier bridge, first resistor, second resistance, capacitor, operational amplifier,
The output end of the input terminal of the rectifier bridge and temperature sensor connects, the first output end of the rectifier bridge and first resistor
One end connection, the other end of the first resistor is connect with one end of the inverting input terminal of operational amplifier, capacitor respectively, described
The other end of capacitor and the output end of operational amplifier connect, one end of the second resistance and the homophase input of operational amplifier
End connection, the other end of the second resistance and the second output terminal of rectifier bridge connect over the ground respectively, the operational amplifier
The connection of the A/D interface of output end and single-chip microcontroller.
Further, the wireless module is GPRS module.
Further, the neural network module is BP neural network module.
The beneficial effects of the utility model are: the invention utilizes acquisition device using neural network module intelligence
Breeding water body quality category assessment result is obtained in the parameter of acquisition, and is shown the assessment result by display module,
Facilitate the quality condition for recognizing current cultivation water body of manager promptly and accurately.
Detailed description of the invention
It, below will be to required in embodiment description in order to illustrate more clearly of the technical scheme in the embodiment of the utility model
Attached drawing to be used is briefly described.Obviously, described attached drawing is a part of the embodiment of the utility model, rather than complete
Portion's embodiment, those skilled in the art without creative efforts, can also be obtained according to these attached drawings it
His design scheme and attached drawing.
Fig. 1 is the system structure diagram of the invention system；
Fig. 2 is the connection schematic diagram of acquisition device；
Fig. 3 is the circuit connection diagram of the first conditioning circuit.
Specific embodiment
It is carried out below with reference to technical effect of the embodiment and attached drawing to the design of the utility model, specific structure and generation
It clearly and completely describes, to be completely understood by the purpose of this utility model, feature and effect.Obviously, described embodiment
It is a part of the embodiment of the utility model, rather than whole embodiments, it is based on the embodiments of the present invention, the skill of this field
Art personnel other embodiments obtained without creative efforts belong to the model of the utility model protection
It encloses.In addition, all connection/connection relationships being previously mentioned in text, not singly refer to that component directly connects, and referring to can be according to specific reality
Situation is applied, by adding or reducing couple auxiliary, to form more preferably coupling structure.Each technology in the invention is special
Sign, can be with combination of interactions under the premise of not conflicting conflict.
Embodiment 1, with reference to Fig. 1, Fig. 2 and Fig. 3, a kind of long-range aquaculture system mass monitoring system, comprising: acquisition
Device 1, remote terminal 3, the remote terminal 3 are equipped with: neural network module 31, display module 32, the neural network module
31 are connect with the acquisition device 1 by internet 2, and the neural network module 31 is connect with the display module 32, described
Neural network module 31 is used for using the temperature of breeding water body, dissolved oxygen, pH value parameter as learning data, and study obtains cultivation water
The assessment result of weight classification, the display module 32 is for showing the assessment result.The acquisition device 1 wraps
Include: temperature sensor 11, dissolved oxygen sensor 12, pH value sensor 13, the first, second, third conditioning circuit 111,121,
131, single-chip microcontroller 14, wireless module 15, serial ports end TXD, RXD of the single-chip microcontroller 14 are connect with wireless module 15 respectively, described
Temperature sensor 11, dissolved oxygen sensor 12, pH value sensor 13 respectively by the first, second, third conditioning circuit 111,
121, it 131 is connect with A/D interface AD0, AD1, AD2 of single-chip microcontroller 14.The temperature sensor 11, dissolved oxygen sensor 12, PH
Value sensor 13 can acquire temperature, dissolved oxygen, the pH value parameter of breeding water body.Wherein, the first, second, third conditioning circuit
111,121,131 circuit structure is identical, and the circuit of conditioning circuit just is discussed in detail by taking the first conditioning circuit 111 as an example here
Structure, first conditioning circuit 111 include: rectifier bridge D, first resistor R1, second resistance R2, capacitor C, operational amplifier
The input terminal of AMP, the rectifier bridge D are connect with the output end of temperature sensor 11, the first output end of the rectifier bridge D and
One end of one resistance R1 connects, the other end of the first resistor R1 respectively with the inverting input terminal of operational amplifier AMP, capacitor
One end of C connects, and the other end of the capacitor C is connect with the output end of operational amplifier AMP, one end of the second resistance R2
It is connect with the non-inverting input terminal of operational amplifier AMP, the other end of the second resistance R2 and the second output terminal point of rectifier bridge D
It does not connect over the ground, the output end of the operational amplifier AMP is connect with the A/D interface AD0 of single-chip microcontroller 14.
Before this system work, need to be trained neural network module 31, the present embodiment is with the cultivation water of turbot
For weight, it is divided into three classes from the breeding water body quality of turbot known to industry specialists empirical data, respectively I class: most suitable
Close the water quality of turbot cultivation；II class: relatively it is suitble to the water quality of turbot cultivation；Group III: be not suitable for the water quality of turbot cultivation；
Temperature corresponding to these three types, dissolved oxygen, pH value supplemental characteristic are respectively, as shown in table 1:
Table 1
| Index | I class | II class | Group III |
| Temperature (DEG C) | 15-20 | 10-15 or 20-23 | <10 or>23 |
| Dissolved oxygen (mg/L) | >6 | 3-6 | <3 |
| PH value | 7.6-8.2 | 6.8-7 or 8.2-8.8 | <6.8 or>8.8 |
The breeding water body quality category and neural network desired output value comparison table of turbot, as shown in table 2:
Table 2
| Breeding water body quality category | Neural network desired output |
| I class | 0.2 |
| II class | 0.4 |
| Group III | 0.6 |
It is defeated with the neural network expectation in table 2 using the temperature of breeding water body, dissolved oxygen, pH value parameter as training sample
As desired value, training obtains that breeding water body quality category assessment knot can be obtained according to temperature, dissolved oxygen, pH value parameter value out
The neural network module 31 of fruit, as optimization, the neural network module 31 is BP neural network module.
When the system works, the temperature sensor 11, dissolved oxygen sensor 12, pH value sensor 13 acquire cultivation respectively
The temperature of water body, dissolved oxygen, pH value signal, and the voltage value for converting the signal into certain rule is respectively transmitted to first,
Two, in third conditioning circuit 111,121,131, first, second, third conditioning circuit 111,121,131 is respectively to voltage
Value is rectified and is integrated to obtain the square-wave signal for being suitble to single-chip microcontroller 14, and the A/D that square-wave signal is respectively transmitted to single-chip microcontroller 14 connects
In mouth AD0, AD1, AD2, the single-chip microcontroller 14 carries out analog-to-digital conversion by A/D interface AD0, AD1, AD2 and obtains temperature, dissolution
The digital value of oxygen, pH value, single-chip microcontroller 14 are uploaded to these digital values in internet 2 by wireless module 15.The nerve net
Network module 31 obtains the digital value of temperature, dissolved oxygen, pH value from the downloading of internet 2, and by study, obtains breeding water body quality
Classification assessment result.The display module 32 shows the breeding water body quality category assessment result, for manager
The quality condition for recognizing breeding water body in time, facilitates management.
As optimization, the wireless module 15 is GPRS module.
The better embodiment of the utility model is illustrated above, but the invention be not limited to it is described
Embodiment, those skilled in the art can also make various equivalent changes without departing from the spirit of the present invention
Type or replacement, these equivalent variation or replacement are all included in the scope defined by the claims of the present application.
Claims (5)
1. a kind of long-range aquaculture system mass monitoring system, comprising: acquisition device, remote terminal, it is characterised in that: institute
State remote terminal to be equipped with: neural network module, display module, the neural network module and the acquisition device pass through internet
Connection, the acquisition device are used to acquire temperature, dissolved oxygen, the pH value parameter of breeding water body, and the neural network module is used for
Using the temperature of breeding water body, dissolved oxygen, pH value parameter as learning data, study obtains breeding water body quality category assessment knot
Fruit, the display module is for showing the assessment result.
2. the long-range aquaculture system mass monitoring system of one kind according to claim 1, which is characterized in that described to adopt
Acquisition means include: temperature sensor, dissolved oxygen sensor, pH value sensor, the first, second, third conditioning circuit, single-chip microcontroller,
Wireless module, the single-chip microcontroller are connect with wireless module by serial ports, and the temperature sensor, dissolved oxygen sensor, pH value pass
Sensor passes through the first, second, third conditioning circuit respectively and connect with single-chip microcontroller.
3. the long-range aquaculture system mass monitoring system of one kind according to claim 2, it is characterised in that: described
One conditioning circuit includes: rectifier bridge, first resistor, second resistance, capacitor, operational amplifier, the input terminal of the rectifier bridge with
The output end of temperature sensor connects, and the first output end of the rectifier bridge and one end of first resistor connect, first electricity
The other end of resistance is connect with one end of the inverting input terminal of operational amplifier, capacitor respectively, the other end of the capacitor and operation
The output end of amplifier connects, and one end of the second resistance and the non-inverting input terminal of operational amplifier connect, second electricity
The other end of resistance and the second output terminal of rectifier bridge connect over the ground respectively, the output end of the operational amplifier and the A/ of single-chip microcontroller
D interface connection.
4. the long-range aquaculture system mass monitoring system of one kind according to claim 2 or 3, it is characterised in that: institute
Stating wireless module is GPRS module.
5. the long-range aquaculture system mass monitoring system of one kind according to claim 4, which is characterized in that the mind
It is BP neural network module through network module.
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| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201820405752.XU CN208188883U (en) | 2018-03-23 | 2018-03-23 | A kind of long-range aquaculture system mass monitoring system |
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| CN201820405752.XU CN208188883U (en) | 2018-03-23 | 2018-03-23 | A kind of long-range aquaculture system mass monitoring system |
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108280517A (en) * | 2018-03-23 | 2018-07-13 | 佛山科学技术学院 | A kind of long-range aquaculture system mass monitoring system |
| CN111950942A (en) * | 2020-10-19 | 2020-11-17 | 平安国际智慧城市科技股份有限公司 | Model-based water pollution risk assessment method and device and computer equipment |
-
2018
- 2018-03-23 CN CN201820405752.XU patent/CN208188883U/en not_active Expired - Fee Related
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108280517A (en) * | 2018-03-23 | 2018-07-13 | 佛山科学技术学院 | A kind of long-range aquaculture system mass monitoring system |
| CN111950942A (en) * | 2020-10-19 | 2020-11-17 | 平安国际智慧城市科技股份有限公司 | Model-based water pollution risk assessment method and device and computer equipment |
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