CN115403222A - Breeding tail water treatment system and method - Google Patents
Breeding tail water treatment system and method Download PDFInfo
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- C02F9/00—Multistage treatment of water, waste water or sewage
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Abstract
The invention discloses a system and a method for treating aquaculture tail water, wherein a first operation parameter is obtained by a machine learning module according to historical data calculation, the pre-control operation of the system for treating aquaculture tail water is realized, the index data of the aquaculture tail water is monitored in real time, and the first operation parameter is correspondingly adjusted based on the data deviation of the index data and the first operation parameter, so that the influence of the quality of inlet water and the treatment effect of the aquaculture tail water on the system for treating aquaculture tail water is reduced, and the real-time performance and the reliability of the treatment of the aquaculture tail water are improved.
Description
Technical Field
The application relates to the technical field of data processing, in particular to a cultivation tail water treatment system and method.
Background
As a new land-based culture mode, the intensive aquaculture has the advantages of high culture density, strong controllability and the like, is rapidly popularized and applied in recent years, and promotes the development and cooperation in the fields of fishery resource maintenance, mariculture, ocean fishery, aquatic product processing and the like. However, the environmental problems associated with mariculture are not negligible. Because the intensive culture mode has high culture density and large bait input amount, a large amount of bait is not absorbed by the aquatic animals, and the residual bait and the excrement of the aquatic animals can cause serious pollution to water and bottom mud. Meanwhile, most aquaculture farms are not provided with tail water treatment facilities, and the aquaculture tail water is directly discharged without treatment or discharged after failing to meet the treatment standard, so that the offshore water eutrophication is caused, and the offshore red tide is frequently caused.
Because the tail water of the seawater culture has the characteristics of high salinity, large displacement and the like, the traditional fresh water culture tail water treatment technology is difficult to be directly applied to the treatment of the tail water of the seawater culture. At present, the mainstream tail water treatment process for mariculture is physical precipitation and artificial wetland, and the key point of tail water treatment structure is to maintain the stability of the quality of inlet water. The existing mariculture tail water treatment technology mainly researches and monitors the change of key parameters in the tail water treatment process in real time, and provides various means for tracking the tail water treatment effect. Because the retention time of tail water in the tail water treatment process is long, the prior mariculture tail water treatment technology needs longer recovery time for adjusting the operation parameters after the water quality is found to be poor, and the water quality cannot be adjusted and controlled in time.
Disclosure of Invention
The present invention aims to solve at least to some extent one of the technical problems existing in the prior art.
Therefore, the embodiment of the invention provides a culture tail water treatment system and method, which improve the real-time performance and reliability of culture tail water treatment.
In order to achieve the technical purpose, the technical scheme adopted by the embodiment of the invention comprises the following steps:
in a first aspect, an embodiment of the present invention provides a culture tail water treatment system, including:
the machine learning module is used for calculating according to historical data to obtain a first operation parameter;
the tail water treatment module is used for carrying out tail water treatment according to the first operation parameter;
the monitoring module is used for monitoring index parameters of tail water in the tail water treatment module in real time;
the first control module is used for comparing the first operation parameter with the index parameter in real time to obtain a data deviation; the data deviation is smaller than or equal to a preset threshold value, and the second operation parameter is a key parameter in the first operation parameter; and adjusting the first operating parameter when the data deviation is greater than the preset threshold value.
In addition, the cultivation tail water treatment system according to the above embodiment of the invention may further have the following additional technical features:
furthermore, in the system for treating the culture tail water, the tail water treatment module comprises an ecological ditch, a sedimentation tank, an ecological purification tank and an aeration tank;
the inlet of the ecological ditch is used for introducing the tail water, the outlet of the ecological ditch is communicated with the inlet of the sedimentation tank, the outlet of the sedimentation tank is communicated with the inlet of the ecological purification tank, the outlet of the ecological purification tank is communicated with the inlet of the aeration tank, and the outlet of the aeration tank is used for discharging the treated tail water.
Further, in one embodiment of the present invention, the monitoring module comprises an acquisition module and a display module;
the acquisition module acquires the index parameters and sends the index parameters to the display module, and the display module displays the index parameters.
Further, in one embodiment of the present invention, the historical data includes historical monitoring data for the monitoring modules and successful case data;
the machine learning module takes the successful case data as a training set to be trained to obtain a third operation parameter;
and the machine learning module takes the historical monitoring data as a verification set to verify and perfect the third operation parameter and generate the first operation parameter.
Further, in one embodiment of the present invention, the system further comprises a second control module;
and the second control module controls the tail water treatment module to perform tail water treatment according to the first operation parameter.
Further, in one embodiment of the present invention, the system further comprises a fresh water reflux module;
and the clear water backflow module is used for performing backflow treatment on the treated tail water discharged by the tail water treatment module.
In a second aspect, an embodiment of the present invention provides a culture tail water treatment method, which is applied to a culture tail water treatment system, where the culture tail water treatment system includes a machine learning module, a tail water treatment module, a monitoring module, and a first control module, and the method includes:
according to historical data, calculating by the machine learning module to obtain a first operation parameter;
according to the first operation parameter, tail water treatment is carried out through the tail water treatment module;
monitoring index parameters of tail water in the tail water treatment module in real time through the monitoring module;
comparing the first operation parameter with the index parameter in real time through the first control module to obtain data deviation;
when the data deviation is smaller than or equal to a preset threshold value, adjusting the second operation parameter through the first control module, wherein the second operation parameter is a key parameter in the first operation parameter;
and when the data deviation is larger than the preset threshold value, adjusting the first operation parameter through the first control module.
Further, in one embodiment of the present invention, the monitoring module includes an acquisition module and a display module;
the real-time monitoring of index parameters of the tail water in the tail water treatment module through the monitoring module comprises the following steps:
acquiring the index parameters through the acquisition module, and sending the index parameters to the display module;
and displaying the index parameter through the display module.
Further, in one embodiment of the present invention, the historical data includes historical monitoring data for the monitoring modules and successful case data;
according to the historical data, a first operation parameter is obtained through calculation of the machine learning module, and the method comprises the following steps:
training the successful case data as a training set to obtain a third operation parameter;
and using the historical monitoring data as a verification set to verify and perfect the third operation parameter to generate the first operation parameter.
Further, in one embodiment of the present invention, the aquaculture tail water treatment system further comprises a second control module;
the tail water treatment by the tail water treatment module according to the first operating parameter comprises:
and controlling the tail water treatment module to perform tail water treatment according to the first operation parameter through the second control module.
The invention has the advantages and beneficial effects that:
according to the embodiment of the invention, the machine learning module is used for calculating the first operation parameter according to the historical data, so that the pre-control operation of the aquaculture tail water treatment system is realized, the index data of the tail water is monitored in real time, and the first operation parameter is correspondingly adjusted based on the data deviation of the index data and the first operation parameter, so that the influence of the quality of the inlet water and the treatment effect of the tail water on the aquaculture tail water treatment system is reduced, and the real-time performance and the reliability of aquaculture tail water treatment are improved.
Drawings
In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the following description is made on the drawings of the embodiments of the present application or the related technical solutions in the prior art, and it should be understood that the drawings in the following description are only for convenience and clarity of describing some embodiments in the technical solutions of the present application, and it is obvious for those skilled in the art that other drawings can be obtained according to these drawings without creative efforts.
FIG. 1 is a schematic structural view of an embodiment of a cultivation tail water treatment system according to the present invention;
FIG. 2 is a schematic flow chart of a method for treating aquaculture tail water according to an embodiment of the present invention.
Detailed Description
Reference will now be made in detail to embodiments of the present invention, examples of which are illustrated in the accompanying drawings, wherein like or similar reference numerals refer to the same or similar elements or elements having the same or similar function throughout. The embodiments described below with reference to the drawings are exemplary only for the purpose of explaining the present application and are not to be construed as limiting the present application. The step numbers in the following embodiments are provided only for convenience of illustration, the order between the steps is not limited at all, and the execution order of each step in the embodiments can be adapted according to the understanding of those skilled in the art.
The terms "first," "second," "third," and "fourth," etc. in the description and claims of the invention and in the accompanying drawings are used for distinguishing between different objects and not for describing a particular order. Furthermore, the terms "include" and "have," as well as any variations thereof, are intended to cover non-exclusive inclusions. For example, a process, method, system, article, or apparatus that comprises a list of steps or elements is not limited to only those steps or elements listed, but may alternatively include other steps or elements not listed, or inherent to such process, method, article, or apparatus.
Reference in the specification to "an embodiment" means that a particular feature, structure, or characteristic described in connection with the embodiment can be included in at least one embodiment of the invention. The appearances of the phrase in various places in the specification are not necessarily all referring to the same embodiment, nor are separate or alternative embodiments mutually exclusive of other embodiments. It is explicitly and implicitly understood by one skilled in the art that the embodiments described herein may be combined with other embodiments.
Because the tail water of the seawater culture has the characteristics of high salinity, large displacement and the like, the traditional fresh water culture tail water treatment technology is difficult to be directly applied to the treatment of the tail water of the seawater culture. The main current seawater culture tail water treatment process is physical precipitation and artificial wetland, and the key point of stable performance of a tail water treatment structure is to maintain the stability of inlet water quality. The existing mariculture tail water treatment technology mainly researches and monitors the change of key parameters in the tail water treatment process in real time, and provides various means for tracking the tail water treatment effect. Because the retention time of tail water in the tail water treatment process is long, the prior mariculture tail water treatment technology needs longer recovery time for adjusting the operation parameters after the water quality is found to be poor, and the water quality cannot be adjusted and controlled in time. Therefore, the invention provides a culture tail water treatment system and a method, a first operation parameter is calculated and obtained through a machine learning module according to historical data, the pre-control operation of the culture tail water treatment system is realized, the index data of the tail water is monitored in real time, and the first operation parameter is correspondingly adjusted based on the data deviation of the index data and the first operation parameter, so that the influence of the quality of inlet water and the treatment effect of the tail water on the culture tail water treatment system is reduced, and the real-time performance and the reliability of the culture tail water treatment are improved.
Hereinafter, a system and a method for treating aquaculture tail water according to an embodiment of the present invention will be described in detail with reference to the accompanying drawings.
Referring to fig. 1, a cultivation tail water treatment system in an embodiment of the present invention includes:
the machine learning module is used for calculating according to historical data to obtain a first operation parameter;
the tail water treatment module is used for carrying out tail water treatment according to the first operation parameter;
the monitoring module is used for monitoring index parameters of tail water in the tail water treatment module in real time;
the first control module is used for comparing the first operation parameter with the index parameter in real time to obtain data deviation; the data deviation is smaller than or equal to a preset threshold value, and the second operation parameter is a key parameter in the first operation parameter; and adjusting the first operating parameter when the data deviation is greater than the preset threshold value.
Optionally, the preset threshold of the embodiment of the present invention may be set to 10%, and the second operation parameter may include the water inlet amount, the backflow amount, and the aeration amount in the first operation parameter.
As an alternative embodiment, the tail water treatment module comprises an ecological ditch, a sedimentation tank, an ecological purification tank and an aeration tank;
the inlet of the ecological ditch is used for introducing the tail water, the outlet of the ecological ditch is communicated with the inlet of the sedimentation tank, the outlet of the sedimentation tank is communicated with the inlet of the ecological purification tank, the outlet of the ecological purification tank is communicated with the inlet of the aeration tank, and the outlet of the aeration tank is used for discharging the treated tail water.
Alternatively, in some embodiments, the size of the settling tank is 1.0m × 2.2m × 1.5m, with an effective volume of 3m 3 (ii) a The size of the aeration tank is 1.0m multiplied by 1.5m, and the effective volume is 2m 3 (ii) a The size of the ecological purifying pool is 2.0m multiplied by 1.5m, and the effective volume is 5.8m 3 (ii) a The size of the ecological ditch is 1.0m multiplied by 1.5m, and the effective volume is 1.3m 3 20cm of fine sand, 30cm of coal cinder, 35cm of broken stone, 15cm of water surface and super height are respectively filled from top to bottom.
Optionally, in some embodiments, spartina alterniflora, eichhornia crassipes, water hyacinth and the like are selected as plants in the ecological purification tank, with a plant density of 10 plants/m 2 The hydraulic load was 0.5m/d.
Optionally, in some embodiments, the influent water quality parameter is: COD concentration is 29.5-36.6 mg/L, and the average value is 32.4mg/L; TP concentration is 0.12-0.73 mg/L, and the average value is 0.53mg/L; the TN concentration is 5.3-13.8 mg/L, and the average value is 8.3mg/L.
As an optional implementation, the monitoring module includes an acquisition module and a display module;
the acquisition module acquires the index parameters and sends the index parameters to the display module, and the display module displays the index parameters.
Optionally, in some embodiments, the collection module comprises water quality and quantity sensors, and the index parameters comprise pH, oxidation-reduction potential, water intake quantity, return water quantity, ammonia nitrogen, nitrate, total phosphorus, dissolved oxygen, COD, and sludge quantity.
Optionally, in some embodiments, the sensor disposed at the inlet of the sedimentation tank collects index parameters including pH, influent water amount, return sludge amount, ammonia nitrogen, nitrate, total phosphorus, and COD; the outlet of the sedimentation tank is provided with a sensor for collecting index parameters including pH value, ammonia nitrogen, nitrate and total phosphorus and COD.
Index parameters collected by a sensor arranged at the inlet of the aeration tank comprise dissolved oxygen, aeration quantity, return water quantity, return sludge quantity, pH value, ammonia nitrogen, nitrate, total phosphorus, COD and sludge concentration; the outlet of the sedimentation tank is provided with a sensor for collecting index parameters including pH value, ammonia nitrogen, nitrate, total phosphorus and COD.
Index parameters collected by a sensor arranged at the inlet of the ecological pool comprise pH value, ammonia nitrogen, nitrate, total phosphorus and COD; the outlet of the sedimentation tank is provided with a sensor for collecting index parameters including pH value, ammonia nitrogen, nitrate, total phosphorus and COD.
It can be understood that, in the embodiment of the present invention, the index parameter collected by the collection module may be subsequently used as a part of the historical data of the machine learning module to perform machine learning calculation on one hand, and is used for comparing with the first operating parameter to perform adjustment of the first operating parameter on the other hand.
As an optional implementation, the historical data includes historical monitoring data of the monitoring module and success case data;
the machine learning module takes the successful case data as a training set to be trained to obtain a third operation parameter;
and the machine learning module takes the historical monitoring data as a verification set to verify and perfect the third operation parameter and generate the first operation parameter.
As an optional implementation, the system further comprises a second control module;
and the second control module controls the tail water treatment module to perform tail water treatment according to the first operation parameter.
Optionally, in some embodiments, the second control module controls the tail water treatment module to perform tail water treatment at the first operating parameter via a solenoid valve.
As an optional embodiment, the system further comprises a clean water backflow module;
and the clear water backflow module is used for performing backflow treatment on the treated tail water discharged by the tail water treatment module.
Next, referring to fig. 1, an embodiment of the present invention provides a cultivation tail water treatment method, where the method is applied to a cultivation tail water treatment system, the cultivation tail water treatment system includes a machine learning module, a tail water treatment module, a monitoring module, and a first control module, and the method includes:
s201, calculating through the machine learning module according to historical data to obtain a first operation parameter;
wherein the historical data comprises historical monitoring data of the monitoring module and successful case data.
Specifically, in the embodiment of the present invention, the machine learning module trains the successful case data as a training set to obtain a third operating parameter, and then verifies and perfects the third operating parameter by using the historical monitoring data as a verification set to generate the first operating parameter.
S202, according to the first operation parameter, tail water treatment is carried out through the tail water treatment module;
wherein, breed tail water processing system still includes the second control module.
Specifically, in the embodiment of the invention, the tail water treatment module is controlled by the second control module to perform tail water treatment according to the first operation parameter.
S203, monitoring index parameters of tail water in the tail water treatment module in real time through the monitoring module;
wherein, the monitoring module comprises an acquisition module and a display module.
Specifically, in the embodiment of the present invention, the acquisition module acquires the index parameter, sends the index parameter to the display module, and displays the index parameter through the display module.
S204, comparing the first operation parameter with the index parameter in real time through the first control module to obtain data deviation;
s205, when the data deviation is smaller than or equal to a preset threshold value, adjusting the second operation parameter through the first control module;
wherein the second operating parameter is a key parameter of the first operating parameter.
And S206, when the data deviation is larger than the preset threshold value, adjusting the first operation parameter through the first control module.
Example 1:
the size of the sedimentation tank is 1.0m multiplied by 2.2m multiplied by 1.5m, and the effective volume is 3m 3 (ii) a The size of the aeration tank is 1.0m multiplied by 1.5m, and the effective volume is 2m 3 (ii) a The size of the ecological purifying pool is 2.0m multiplied by 1.5m, and the effective volume is 5.8m 3 (ii) a The ecological ditch has a size of 1.0m × 1.0m × 1.5m and an effective volume of 1.3m 3 20cm of fine sand, 30cm of coal cinder, 35cm of broken stone, 15cm of water surface and super height are respectively filled from top to bottom. The spartina alterniflora, the water hyacinth and the like are selected as plants in the ecological purification tank, and the plant density is 10 plants/m 2 The hydraulic load was 0.5m/d. The parameters of the inlet water quality are as follows: COD concentration is 29.5-36.6 mg/L, and the average value is 32.4mg/L; TP concentration is 0.12-0.73 mg/L, and the average value is 0.53mg/L; the TN concentration is 5.3-13.8 mg/L, and the average value is 8.3mg/L.
Index parameters collected by a sensor arranged at the inlet of the sedimentation tank comprise pH value, inflow water quantity, return sludge quantity, ammonia nitrogen, nitrate, total phosphorus and COD; the outlet of the sedimentation tank is provided with a sensor for collecting index parameters including pH value, ammonia nitrogen, nitrate and total phosphorus and COD.
Index parameters collected by a sensor arranged at the inlet of the aeration tank comprise dissolved oxygen, aeration quantity, return water quantity, return sludge quantity, pH value, ammonia nitrogen, nitrate, total phosphorus, COD and sludge concentration; the outlet of the sedimentation tank is provided with a sensor for collecting index parameters including pH value, ammonia nitrogen, nitrate, total phosphorus and COD.
Index parameters collected by a sensor arranged at the inlet of the ecological pool comprise pH value, ammonia nitrogen, nitrate, total phosphorus and COD; the outlet of the sedimentation tank is provided with a sensor for collecting index parameters including pH value, ammonia nitrogen, nitrate, total phosphorus and COD.
Based on the arrangement, the aquaculture tail water treatment system and the aquaculture tail water treatment method are adopted to treat aquaculture tail water.
Example 2:
the parameters of the inlet water quality are as follows: the COD concentration is 21.5-26.6 mg/L, and the average value is 23.4mg/L; TP concentration is 0.09-0.53 mg/L, and the average value is 0.43mg/L; the TN concentration is 4.6-10.1 mg/L, and the average value is 6.3mg/L. The other settings of example 2 were the same as those of example 1.
Example 3:
the parameters of the water quality of the inlet water are as follows: COD concentration is 40.5-48.4 mg/L, and the average value is 46.3mg/L; TP concentration is 0.17-0.93 mg/L, and the average value is 0.62mg/L; the TN concentration is 5.4-12.4 mg/L, and the average value is 8.6mg/L. The other settings of example 3 were the same as those of example 1.
Comparative example 1:
based on the setting of the embodiment 1, the traditional cultivation tail water treatment method is adopted to carry out cultivation tail water treatment.
Comparative example 2:
based on the setting of the embodiment 2, the traditional cultivation tail water treatment method is adopted to carry out cultivation tail water treatment.
Comparative example 3:
based on the setting of the embodiment 3, the traditional cultivation tail water treatment method is adopted to carry out cultivation tail water treatment.
The treatment effects of examples 1 to 3 and comparative examples 1 to 3 are shown in Table 1:
TABLE 1
| Examples | COD removal rate | Removal rate of TN | TP removal Rate |
| Example 1 | 78～82％ | 62～68％ | 76～79％ |
| Example 2 | 71～76％ | 52～61％ | 66～73％ |
| Example 3 | 70～78％ | 50～58％ | 62～9％ |
| Comparative example 1 | 52～68％ | 42～57％ | 46～59％ |
| Comparative example 2 | 44～57％ | 40～59％ | 36～61％ |
| Comparative example 3 | 42～56％ | 33～47％ | 38～54％ |
As can be seen from Table 1, when the quality of the inlet water changes, the removal rates of COD, TN and TP of the outlet water treated by the aquaculture tail water treatment system provided by the embodiment of the invention are relatively stable, and the change range is mostly within 5%. In a pilot experiment, the culture tail water treatment system provided by the embodiment of the invention stably runs for more than 180 days.
In the comparative example, the water outlet efficiency is lower than that of the culture tail water treatment system in the embodiment of the invention, the change is large, and the change amplitude of most of the outlet water is more than 10%. In the pilot experiment, the water quality of the system is deteriorated and the system cannot be operated after the comparative example is operated for 55 days.
In conclusion, the first operation parameter is calculated and obtained through the machine learning module according to the historical data, the pre-control operation of the aquaculture tail water treatment system is realized, the index data of the tail water is monitored in real time, and the first operation parameter is correspondingly adjusted based on the data deviation between the index data and the first operation parameter, so that the influence of the quality of the inlet water and the tail water treatment effect on the aquaculture tail water treatment system is reduced, and the real-time performance and the reliability of aquaculture tail water treatment are improved.
The contents in the above method embodiments are all applicable to the present system embodiment, the functions specifically implemented by the present system embodiment are the same as those in the above method embodiment, and the beneficial effects achieved by the present system embodiment are also the same as those achieved by the above method embodiment.
In alternative embodiments, the functions/acts noted in the block diagrams may occur out of the order noted in the operational illustrations. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality/acts involved. Furthermore, the embodiments presented and described in the flowcharts of the present application are provided by way of example in order to provide a more comprehensive understanding of the technology. The disclosed methods are not limited to the operations and logic flows presented herein. Alternative embodiments are contemplated in which the order of various operations is changed and in which sub-operations described as part of larger operations are performed independently.
Furthermore, although the present application is described in the context of functional modules, it should be understood that, unless otherwise stated to the contrary, one or more of the functions and/or features may be integrated in a single physical device and/or software module, or one or more functions and/or features may be implemented in separate physical devices or software modules. It will also be appreciated that a detailed discussion regarding the actual implementation of each module is not necessary for an understanding of the present application. Rather, the actual implementation of the various functional modules in the apparatus disclosed herein will be understood within the ordinary skill of an engineer, given the nature, function, and internal relationship of the modules. Accordingly, those skilled in the art can, using ordinary skill, practice the present application as set forth in the claims without undue experimentation. It is also to be understood that the specific concepts disclosed are merely illustrative of and not intended to limit the scope of the application, which is defined by the appended claims and their full scope of equivalents.
It should be understood that portions of the present application may be implemented in hardware, software, firmware, or a combination thereof. In the above embodiments, the various steps or methods may be implemented in software or firmware stored in memory and executed by a suitable program execution system. For example, if implemented in hardware, as in another embodiment, any one or combination of the following techniques, which are known in the art, may be used: a discrete logic circuit having a logic gate circuit for implementing a logic function on a data signal, an application specific integrated circuit having an appropriate combinational logic gate circuit, a Programmable Gate Array (PGA), a Field Programmable Gate Array (FPGA), or the like.
In the foregoing description of the specification, reference to the description of "one embodiment/example," "another embodiment/example," or "certain embodiments/examples," etc., means that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the application. In this specification, schematic representations of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples.
While embodiments of the present application have been shown and described, it will be understood by those of ordinary skill in the art that: numerous changes, modifications, substitutions and alterations can be made to the embodiments without departing from the principles and spirit of the application, the scope of which is defined by the claims and their equivalents.
While the present application has been described with reference to the preferred embodiments, it will be understood by those skilled in the art that various changes in form and details may be made therein without departing from the spirit and scope of the invention as defined by the appended claims.
Claims (10)
1. A culture tail water treatment system, comprising:
the machine learning module is used for calculating according to historical data to obtain a first operation parameter;
the tail water treatment module is used for carrying out tail water treatment according to the first operation parameter;
the monitoring module is used for monitoring index parameters of tail water in the tail water treatment module in real time;
the first control module is used for comparing the first operation parameter with the index parameter in real time to obtain data deviation; the data deviation is smaller than or equal to a preset threshold value, and the second operation parameter is a key parameter in the first operation parameter; and adjusting the first operating parameter when the data deviation is greater than the preset threshold value.
2. The aquaculture tail water treatment system of claim 1, wherein the tail water treatment module comprises an ecological ditch, a sedimentation tank, an ecological purification tank and an aeration tank;
the inlet of the ecological ditch is used for introducing the tail water, the outlet of the ecological ditch is communicated with the inlet of the sedimentation tank, the outlet of the sedimentation tank is communicated with the inlet of the ecological purification tank, the outlet of the ecological purification tank is communicated with the inlet of the aeration tank, and the outlet of the aeration tank is used for discharging the treated tail water.
3. The aquaculture tail water treatment system of claim 1, wherein the monitoring module comprises an acquisition module and a display module;
the acquisition module acquires the index parameters and sends the index parameters to the display module, and the display module displays the index parameters.
4. The aquaculture tail water treatment system of claim 1, wherein the historical data comprises historical monitoring data of the monitoring modules and success case data;
the machine learning module takes the successful case data as a training set to be trained to obtain a third operation parameter;
and the machine learning module takes the historical monitoring data as a verification set to verify and perfect the third operation parameter and generate the first operation parameter.
5. The aquaculture tail water treatment system of claim 1, further comprising a second control module;
and the second control module controls the tail water treatment module to perform tail water treatment according to the first operation parameter.
6. The aquaculture tail water treatment system of claim 1, further comprising a clean water return module;
and the clear water backflow module is used for performing backflow treatment on the treated tail water discharged by the tail water treatment module.
7. A cultivation tail water treatment method is applied to a cultivation tail water treatment system, the cultivation tail water treatment system comprises a machine learning module, a tail water treatment module, a monitoring module and a first control module, and the method comprises the following steps:
according to historical data, calculating by the machine learning module to obtain a first operation parameter;
according to the first operation parameter, tail water treatment is carried out through the tail water treatment module;
monitoring index parameters of tail water in the tail water treatment module in real time through the monitoring module;
comparing the first operation parameter with the index parameter in real time through the first control module to obtain data deviation;
when the data deviation is smaller than or equal to a preset threshold value, adjusting the second operation parameter through the first control module, wherein the second operation parameter is a key parameter in the first operation parameter;
and when the data deviation is larger than the preset threshold value, adjusting the first operation parameter through the first control module.
8. The aquaculture tail water treatment method according to claim 7, wherein the monitoring module comprises an acquisition module and a display module;
the index parameters of the tail water in the tail water treatment module, which are monitored in real time by the monitoring module, comprise:
acquiring the index parameters through the acquisition module, and sending the index parameters to the display module;
and displaying the index parameters through the display module.
9. The aquaculture tail water treatment method according to claim 7, wherein the historical data comprises historical monitoring data of the monitoring modules and success case data;
according to the historical data, a first operation parameter is obtained through calculation of the machine learning module, and the method comprises the following steps:
training the successful case data as a training set to obtain a third operation parameter;
and using the historical monitoring data as a verification set to verify and perfect the third operation parameter to generate the first operation parameter.
10. The cultivation tail water treatment method as claimed in claim 7, wherein the cultivation tail water treatment system further comprises a second control module;
the tail water treatment by the tail water treatment module according to the first operating parameter comprises:
and controlling the tail water treatment module to perform tail water treatment according to the first operation parameter through the second control module.
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| CN115403222B (en) | 2023-11-14 |
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