Water quality measurement and control system for fishery breeding

Abstract

The invention discloses a water quality measurement and control system for fishery breeding, which comprises a data acquisition module, a water quality management module and an abnormal early warning module, and is characterized in that the data acquisition module is used for collecting comprehensive detection data of water quality in a breeding pond and inputting comprehensive information and historical processing data of the breeding pond into the system; the water quality management module is used for analyzing abnormal parameters of water quality, further analyzing mutual influence among the abnormal parameters of the water quality, determining primary and secondary relations of the abnormal parameters according to an analysis result, calculating the concentration and the feeding amount of a water quality conditioning agent according to the abnormal parameters, calculating the operation power of oxygen pumping equipment and marking abnormal areas in a culture pond; a water quality regulator is sprayed according to the abnormal parameters of the abnormal area in the culture pond to regulate and control the water quality, the abnormity early warning module is used for reminding a farmer through the user side when the water quality of the culture pond is abnormal, and the system has the advantages of being high in accuracy and efficiency.

Description

Technical Field

[0001] The invention relates to the technical field of water quality measurement and control, and in particular to a water quality measurement and control system for fishery breeding. Background Art

[0002] With the rapid development of Internet technology, my country's fishery farming has begun to use scientific and technological achievements to improve the quality of aquaculture water, making the water quality more conducive to fish growth and achieving the goal of increasing production.

[0003] At present, most fishery farmers still use simple detection equipment combined with farming experience to judge changes in water quality and then improve water quality based on experience. However, due to the mutual influence of abnormal aquaculture water quality, there are certain differences in water quality parameters in the aquaculture pond area. The existing technology cannot accurately control the equipment to regulate the water quality, resulting in poor accuracy in the regulation of water quality parameters. Moreover, most farmers manually analyze water quality problems and calculate the amount of regulators to be added, and then spray the agents, resulting in low treatment efficiency and poor accuracy. Therefore, it is very necessary to design a water quality measurement and control system with high accuracy and efficiency for fishery farming. Summary of the invention

[0004] The purpose of the present invention is to provide a water quality measurement and control system for fishery farming to solve the problems raised in the above background technology.

[0005] In order to solve the above technical problems, the present invention provides the following technical solutions: a water quality measurement and control system for fishery breeding, comprising a data acquisition module, a water quality management module and an abnormal warning module, characterized in that: the data acquisition module is used to collect comprehensive detection data of water quality in the breeding pond, and enter the comprehensive information and historical processing data of the breeding pond into the system; the water quality management module is used to analyze abnormal parameters of water quality, further analyze the mutual influence between abnormal parameters of water quality, determine the primary and secondary relationship of abnormal parameters according to the analysis results, calculate the concentration and feeding amount of water quality regulator according to the abnormal parameters, calculate the feeding speed and feeding amount of feeding equipment, calculate the operating power of oxygenating equipment, mark abnormal areas in the breeding pond, spray water quality regulator according to the abnormal parameters of the abnormal area in the breeding pond to regulate the water quality, the abnormal warning module is used to remind the breeder through the user terminal when the water quality of the breeding pond is abnormal, and the data acquisition module, the water quality management module and the water quality regulation module are connected to each other in communication; The water quality detection module includes a water quality parameter detection submodule, an abnormal parameter analysis submodule and a parameter prediction submodule. The water quality parameter detection submodule is used to detect in real time whether the water quality parameters of each area in the breeding pond are abnormal. The abnormal parameter analysis submodule is used to analyze the mutual influence between the abnormal parameters. The parameter prediction submodule is used to train a model based on the mutual influence relationship between the abnormal parameters, and use the model to predict the changes in the water quality parameters in the breeding pond; The equipment control module includes a dosage analysis submodule, an equipment power calculation submodule and an equipment regulation submodule. The dosage analysis submodule is used to analyze the parameter changes of water quality and calculate the dosage of feed and water quality regulator according to the analysis results. The equipment power calculation submodule is used to analyze the dissolved oxygen content in each area of ​​the breeding pond and calculate the operating power of the oxygenation equipment according to the analysis results. The equipment regulation submodule is used to mark the area where the water quality parameters are abnormal, and control the water quality regulator spraying speed of the UAV according to the impact degree and location of the abnormal area.

[0006] According to the above technical solution, the data acquisition module includes a sensor module, a comprehensive information input module for aquaculture ponds and a historical processing data input module. The sensor module is used to collect comprehensive water quality detection data of the aquaculture pond in real time. The comprehensive information input module for aquaculture ponds is used to enter the comprehensive information of the aquaculture ponds into the system. The historical processing data entry module is used to enter abnormal water quality data of the aquaculture ponds into the system.

[0007] According to the above technical solution, the water quality management module includes a water quality detection module, which is used to detect water quality parameters in the breeding pond in real time, analyze whether the water quality parameters are abnormal, and further analyze the mutual influence between abnormal parameters.

[0008] According to the above technical solution, the water quality management module also includes an equipment control module, which is used to analyze the abnormal degree of water quality abnormal parameters in each area, calculate the preparation concentration of the water quality regulator, the feeding speed and the operating power of the oxygenation equipment according to the abnormal degree, and adjust the equipment according to the calculation results to improve the water quality of the breeding pond.

[0009] According to the above technical solution, the abnormal warning module includes a communication module and a warning module, the communication module is used to communicate with the user end, and the warning module is used to issue an alarm when the water quality of the breeding pond is abnormal.

[0010] According to the above technical solution, the operation method of the water quality measurement and control system mainly includes the following steps: Step S1: Collect the comprehensive water quality detection data of each area of ​​the breeding pond in real time through the sensor module, enter the comprehensive information of the breeding pond into the system through the breeding pond comprehensive information input module, and enter the abnormal water quality of the breeding pond into the system through the historical processing data input module; Step S2: After the data collection is completed, the system starts the water quality detection module and starts to analyze the water quality parameters of each area of ​​the aquaculture pond. According to the analysis results, the mutual influence between abnormal parameters is further analyzed, and the model is trained according to the analysis results to predict the changes in water quality parameters; Step S3: When regulating the water quality, the system starts the equipment control module, calculates the concentration of the water quality regulator, the feeding speed and the operating power of the oxygenator according to the real-time abnormal parameters and the predicted abnormal parameters, and regulates the equipment according to the calculation results; Step S4: When dispensing the water quality regulator, the system marks the area with abnormal water quality parameters, and calculates the spraying speed of the unmanned sprayer according to the abnormal parameter value of the abnormal area; Step S5: When the water quality parameters in the breeding pond are abnormal, a connection is established with the user end through the communication module, and an alarm is sent to the user end.

[0011] According to the above technical solution, step S2 further includes the following steps: Step S21: Acquire historical processing data of water quality in the aquaculture pond, identify abnormal water quality parameter sets in each area in the historical processing data, identify abnormal parameter combinations and corresponding abnormal parameter features; Step S22: Identify the mutual influence relationship between each abnormal parameter in the water quality abnormal parameter set of each area, construct an abnormal parameter influence knowledge map according to the identified influence relationship, use the abnormal parameter combination, abnormal parameter characteristics and the mutual influence relationship between the abnormal parameters as sample data, retrieve the corresponding water quality parameter prediction model in the database, train the water quality parameter prediction model, and use the water quality parameter prediction model to predict the water quality parameters of each area of ​​the aquaculture pond; Step S23: Obtain the sensor data of the breeding pond, identify the water quality parameters of each area of ​​the breeding pond, identify the actual stamps of the water quality parameters and the corresponding values, establish a coordinate system, mark the water quality parameters in the coordinate system, connect the water quality parameter points in sequence, construct a water quality parameter change line graph, identify the change characteristics of the water quality parameter change line graph, and predict the water quality parameters of each area of ​​the breeding pond according to the change characteristics; Step S24: Calculate the difference between the water quality parameters predicted by the prediction model. When the difference is less than the minimum threshold, select the average of the two as the prediction value. When the difference is greater than the minimum threshold and less than the maximum threshold, perform weighted fusion on the two prediction values ​​and select the weighted fusion value as the prediction value. When the difference is greater than the maximum threshold, identify the relationship between the parameters in the prediction parameter set, and compare the database based on the relationship between the parameters. If the matching degree is less than the threshold, delete the prediction value. Otherwise, select the prediction parameter as the prediction value.

[0012] According to the above technical solution, step S3 further includes the following steps: Step S31: Obtain the predicted values ​​of water quality parameters, identify the predicted values ​​of dissolved oxygen, pH value and ammonia nitrogen concentration in the data, retrieve the corresponding water quality parameter standards in the database, compare the predicted value of pH value with the water quality parameter standards, if the predicted value of pH value is greater than the minimum value and less than the maximum value, then retrieve the corresponding parameter standard influence coefficient α in the database according to the difference between the predicted value of pH value and the optimal value of pH, otherwise the system continues to detect; Step S32: Identify the predicted oxygen capacity value m of the target area in the aquaculture pond, and calculate the difference between the predicted oxygen capacity value and the parameter standard by the formula Q=m-α M, where Q represents the difference between the predicted oxygen capacity value and the parameter standard, and M represents the parameter standard value. If the difference is less than the threshold, it is marked as an abnormal parameter, otherwise the system continues to detect; Step S33: Identify abnormal parameters, retrieve the oxygen capacity parameter change line graph in the corresponding period in the database, identify the change characteristics of oxygen capacity in the line graph, if the change characteristic is growth, retrieve the corresponding growth rate in the database according to the change characteristic, otherwise retrieve the corresponding reduction rate in the database, and calculate the time required for oxygen capacity to grow to the parameter standard through the formula = , where Indicates the time required for oxygen capacity to increase to the parameter standard. Indicates the growth rate of the target area of ​​the aquaculture pond. When the oxygen capacity is less than the threshold set by the system, the oxygen supply speed of the oxygen supply equipment required within the set time is calculated by the formula = + , where Indicates the oxygen supply speed of the oxygen supply equipment required for the oxygen capacity within the set time. Indicates the oxygen supply time set by the system. Indicates the growth rate of the target area of ​​the aquaculture pond. According to the calculated oxygenation speed of the required oxygenation equipment, the corresponding equipment operating power is retrieved from the database, and the equipment is started for oxygenation according to the equipment operating power. Otherwise, the system continues to detect.

[0013] According to the above technical solution, in step S33, the predicted value of the ammonia nitrogen concentration in the breeding pond is obtained and compared with the database. When the ammonia nitrogen concentration is greater than the system set threshold, the oxygen capacity of the breeding pond is detected. If the oxygen capacity is consistent with the parameter standard, the corresponding feeding reduction amount in the database is retrieved according to the difference between the ammonia nitrogen concentration and the parameter standard, and the feeding amount is reduced. Otherwise, the oxygen supply equipment is started to compensate the oxygen in the breeding pond.

[0014] According to the above technical solution, in step S4, the abnormal water quality parameter H of each area in the breeding pond is identified, and the average value of the abnormal water quality parameter is calculated by the formula According to the average of water quality parameters, the corresponding water quality regulator concentration in the database is retrieved, and the water quality abnormal parameter deviation coefficient is calculated by the formula , where P represents the water quality abnormal parameter deviation coefficient, j=1,2,3......n, and the corresponding influence coefficient β on the speed of the unmanned sprayer is retrieved from the database according to the water quality abnormal parameter deviation coefficient, and the speed of the unmanned sprayer over the target area is calculated by the formula =β , where Indicates the speed of the unmanned sprayer over the target area. It indicates the rated speed of the unmanned sprayer. According to the flight speed of the unmanned sprayer, the best spraying route is planned for the unmanned sprayer to spray the water quality regulator on the target area.

[0015] Compared with the prior art, the beneficial effects achieved by the present invention are as follows: the present invention can reduce the deviation of the water quality parameter prediction value by comparing the difference between the model prediction value and the trend prediction value and correcting the prediction parameter value, thereby greatly improving the accuracy of the system; by predicting the water quality parameters, the equipment can be started in advance to adjust the water quality in the breeding pond, reducing the water quality control time, avoiding the impact of water quality changes on the cultured, thereby reducing losses and improving efficiency; by analyzing the impact of the pH value in the water quality parameters on the water quality parameter standards, the water quality can be accurately controlled to make it more suitable for the growth of the cultured, thereby greatly improving The accuracy of the system is improved by analyzing the changing trend of oxygen capacity in the target area and then calculating the required oxygenation speed. The power of the oxygenation equipment is set according to the oxygenation speed to ensure that the oxygenation equipment can quickly and accurately replenish oxygen to the target area, further improving the accuracy and efficiency of the system. By analyzing the ammonia nitrogen content in the breeding pond and then reducing the amount of feed, it can avoid overfeeding and abnormal water quality parameters, thereby reducing breeding costs and avoiding abnormal water quality. By adjusting the driving speed of the unmanned sprayer, it can ensure that the driving speed is slower in the target area with serious water quality parameters, ensuring the spraying of the correct dose of regulator. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] The accompanying drawings are used to provide a further understanding of the present invention and constitute a part of the specification. Together with the embodiments of the present invention, they are used to explain the present invention and do not constitute a limitation of the present invention. In the accompanying drawings: Figure 1 It is a schematic diagram of the system module composition of the present invention. DETAILED DESCRIPTION

[0017] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0018] See also Figure 1 The present invention provides a technical solution: a water quality measurement and control system for fishery breeding, comprising a data acquisition module, a water quality management module and an abnormal warning module, characterized in that: the data acquisition module is used to collect comprehensive detection data of water quality in the breeding pond, and enter the comprehensive information and historical processing data of the breeding pond into the system; the water quality management module is used to analyze abnormal parameters of water quality, further analyze the mutual influence between abnormal parameters of water quality, determine the primary and secondary relationship of abnormal parameters according to the analysis results, calculate the concentration and feeding amount of water quality regulator according to the abnormal parameters, calculate the feeding speed and feeding amount of feeding equipment, calculate the operating power of oxygenating equipment, mark abnormal areas in the breeding pond, spray water quality regulator according to the abnormal parameters of the abnormal area in the breeding pond to regulate the water quality, the abnormal warning module is used to remind the breeder through the user terminal when the water quality of the breeding pond is abnormal, and the data acquisition module, the water quality management module and the water quality regulation module are connected to each other in communication; The water quality detection module includes a water quality parameter detection submodule, an abnormal parameter analysis submodule and a parameter prediction submodule. The water quality parameter detection submodule is used to detect in real time whether the water quality parameters in each area of ​​the breeding pond are abnormal. The abnormal parameter analysis submodule is used to analyze the mutual influence between the abnormal parameters. The parameter prediction submodule is used to train a model based on the mutual influence relationship between the abnormal parameters and use the model to predict the changes in the water quality parameters in the breeding pond. The equipment control module includes a dosage analysis submodule, an equipment power calculation submodule and an equipment regulation submodule. The dosage analysis submodule is used to analyze the parameter changes of water quality and calculate the dosage of feed and water quality regulator according to the analysis results. The equipment power calculation submodule is used to analyze the dissolved oxygen content in each area of ​​the breeding pond and calculate the operating power of the oxygenation equipment according to the analysis results. The equipment regulation submodule is used to mark areas with abnormal water quality parameters and control the water quality regulator spraying speed of the drone according to the impact degree and location of the abnormal area.

[0019] The data acquisition module includes a sensor module, a comprehensive information entry module for aquaculture ponds and a historical processing data entry module. The sensor module is used to collect comprehensive water quality detection data of aquaculture ponds in real time. The comprehensive information entry module for aquaculture ponds is used to enter comprehensive information of aquaculture ponds into the system. The historical processing data entry module is used to enter abnormal water quality data of aquaculture ponds into the system.

[0020] The water quality management module includes a water quality detection module, which is used to detect the water quality parameters in the breeding pond in real time, analyze whether the water quality parameters are abnormal, and further analyze the mutual influence between abnormal parameters.

[0021] The water quality management module also includes an equipment control module, which is used to analyze the abnormal degree of water quality parameters in each area, calculate the preparation concentration of water quality regulators, feeding speed and operating power of oxygen equipment according to the abnormal degree, and adjust the equipment to improve the water quality of the breeding pond according to the calculation results.

[0022] The abnormal warning module includes a communication module and an early warning module. The communication module is used to communicate with the user end, and the early warning module is used to issue an alarm when the water quality of the breeding pond is abnormal.

[0023] The operation method of the water quality measurement and control system mainly includes the following steps: Step S1: Collect the comprehensive water quality detection data of each area of ​​the breeding pond in real time through the sensor module, enter the comprehensive information of the breeding pond into the system through the breeding pond comprehensive information input module, and enter the abnormal water quality of the breeding pond into the system through the historical processing data input module; Step S2: After the data collection is completed, the system starts the water quality detection module and starts to analyze the water quality parameters of each area of ​​the aquaculture pond. According to the analysis results, the mutual influence between abnormal parameters is further analyzed, and the model is trained according to the analysis results to predict the changes in water quality parameters; Step S3: When regulating the water quality, the system starts the equipment control module, calculates the concentration of the water quality regulator, the feeding speed and the operating power of the oxygenator according to the real-time abnormal parameters and the predicted abnormal parameters, and regulates the equipment according to the calculation results; Step S4: When dispensing the water quality regulator, the system marks the area with abnormal water quality parameters, and calculates the spraying speed of the unmanned sprayer according to the abnormal parameter value of the abnormal area; Step S5: When the water quality parameters in the breeding pond are abnormal, a connection is established with the user end through the communication module, and an alarm is sent to the user end.

[0024] Step S2 further comprises the following steps: Step S21: Acquire historical processing data of water quality in the aquaculture pond, identify abnormal water quality parameter sets in each area in the historical processing data, identify abnormal parameter combinations and corresponding abnormal parameter features; Step S22: Identify the mutual influence relationship between each abnormal parameter in the water quality abnormal parameter set of each area, construct an abnormal parameter influence knowledge map according to the identified influence relationship, use the abnormal parameter combination, abnormal parameter characteristics and the mutual influence relationship between the abnormal parameters as sample data, retrieve the corresponding water quality parameter prediction model in the database, train the water quality parameter prediction model, and use the water quality parameter prediction model to predict the water quality parameters of each area of ​​the aquaculture pond; Step S23: Acquire the sensor data of the breeding pond, identify the water quality parameters of each area of ​​the breeding pond, identify the actual stamps of the water quality parameters and the corresponding values, establish a coordinate system, mark the water quality parameters in the coordinate system, connect the water quality parameter points in sequence, construct a water quality parameter change line graph, identify the change characteristics of the water quality parameter change line graph, predict the water quality parameters of each area of ​​the breeding pond according to the change characteristics, and by comparing the difference between the model prediction value and the trend prediction value and correcting the prediction parameter value, the deviation of the water quality parameter prediction value can be reduced, thereby greatly improving the accuracy of the system; Step S24: Calculate the difference between the water quality parameters predicted by the prediction model. When the difference is less than the minimum threshold, select the average value of the two as the prediction value. When the difference is greater than the minimum threshold and less than the maximum threshold, perform weighted fusion on the two prediction values ​​and select the weighted fusion value as the prediction value. When the difference is greater than the maximum threshold, identify the relationship between the parameters in the prediction parameter set, and compare the database according to the relationship between the parameters. If the matching degree is less than the threshold, delete the prediction value. Otherwise, select the prediction parameter as the prediction value. By predicting the water quality parameters, the equipment can be started in advance to adjust the water quality in the breeding pond, reduce the water quality control time, avoid the impact of water quality changes on the breeding, thereby reducing losses and improving efficiency.

[0025] Step S3 further comprises the following steps: Step S31: Obtain the predicted values ​​of water quality parameters, identify the predicted values ​​of dissolved oxygen, pH value and ammonia nitrogen concentration in the data, retrieve the corresponding water quality parameter standards in the database, compare the predicted value of pH value with the water quality parameter standards, if the predicted value of pH value is greater than the minimum value and less than the maximum value, retrieve the corresponding parameter standard influence coefficient α in the database according to the difference between the predicted value of pH value and the optimal value of pH, otherwise the system continues to detect, by analyzing the influence of pH value in water quality parameters on water quality parameter standards, the water quality can be accurately regulated to make it more suitable for the growth of aquaculture, thereby greatly improving the accuracy of the system; Step S32: Identify the predicted oxygen capacity value m of the target area in the aquaculture pond, and calculate the difference between the predicted oxygen capacity value and the parameter standard by the formula Q=m-α M, where Q represents the difference between the predicted oxygen capacity value and the parameter standard, and M represents the parameter standard value. If the difference is less than the threshold, it is marked as an abnormal parameter, otherwise the system continues to detect; Step S33: Identify abnormal parameters, retrieve the oxygen capacity parameter change line graph in the corresponding period in the database, identify the change characteristics of oxygen capacity in the line graph, if the change characteristic is growth, retrieve the corresponding growth rate in the database according to the change characteristic, otherwise retrieve the corresponding reduction rate in the database, and calculate the time required for oxygen capacity to grow to the parameter standard through the formula = , where Indicates the time required for oxygen capacity to increase to the parameter standard. Indicates the growth rate of the target area of ​​the aquaculture pond. When the oxygen capacity is less than the threshold set by the system, the oxygen supply speed of the oxygen supply equipment required within the set time is calculated by the formula = + , where Indicates the oxygen supply speed of the oxygen supply equipment required for the oxygen capacity within the set time. Indicates the oxygen supply time set by the system. It indicates the growth rate of the target area of ​​the aquaculture pond. According to the calculated oxygenation speed of the required oxygenation equipment, the corresponding equipment operating power in the database is retrieved, and the equipment is started for oxygenation according to the equipment operating power. Otherwise, the system continues to detect. By analyzing the changing trend of the oxygen capacity in the target area, the required oxygenation speed is calculated, and the power of the oxygenation equipment is set according to the oxygenation speed. This can ensure that the oxygenation equipment can quickly and accurately replenish oxygen for the target area, further improving the accuracy and efficiency of the system.

[0026] In step S33, the predicted value of the ammonia nitrogen concentration in the breeding pond is obtained and compared with the database. When the ammonia nitrogen concentration is greater than the system set threshold, the oxygen capacity of the breeding pond is detected. If the oxygen capacity is consistent with the parameter standard, the corresponding feed reduction amount in the database is retrieved according to the difference between the ammonia nitrogen concentration and the parameter standard, and the feed amount is reduced. Otherwise, the oxygenation equipment is started to compensate the oxygen in the breeding pond. By analyzing the ammonia nitrogen content in the breeding pond and then reducing the feed amount, overfeeding can be avoided, which leads to abnormal water quality parameters, thereby reducing breeding costs and avoiding abnormal water quality.

[0027] In step S4, the water quality abnormality parameter H of each area in the aquaculture pond is identified, and the average value of the water quality abnormality parameter is calculated by the formula According to the average of water quality parameters, the corresponding water quality regulator concentration in the database is retrieved, and the water quality abnormal parameter deviation coefficient is calculated by the formula , where P represents the water quality abnormal parameter deviation coefficient, j=1,2,3.....n, and the corresponding influence coefficient β on the speed of the unmanned sprayer is retrieved from the database according to the water quality abnormal parameter deviation coefficient, and the speed of the unmanned sprayer over the target area is calculated by the formula =β , where Indicates the speed of the unmanned sprayer over the target area. It indicates the rated driving speed of the unmanned sprayer. The best spraying route is planned for the unmanned sprayer according to its flight speed. Water quality regulator is sprayed on the target area. By adjusting the driving speed of the unmanned sprayer, the driving speed can be slowed down in the target area with abnormal water quality parameters to ensure the accurate dosage of regulator is sprayed.

[0028] It should be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device.

[0029] Finally, it should be noted that the above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art can still modify the technical solutions described in the aforementioned embodiments or replace some of the technical features therein by equivalents. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. A water quality measurement and control system for fishery farming, comprising a data acquisition module, a water quality management module and an abnormal warning module, characterized in that: The data acquisition module is used to collect comprehensive detection data of water quality in the breeding pond, and input the comprehensive information and historical processing data of the breeding pond into the system. The water quality management module is used to analyze abnormal parameters of water quality, further analyze the mutual influence between abnormal parameters of water quality, determine the primary and secondary relationship of abnormal parameters according to the analysis results, calculate the concentration and feeding amount of water quality regulator according to the abnormal parameters, calculate the feeding speed and feeding amount of feeding equipment, calculate the operating power of oxygenating equipment, mark abnormal areas in the breeding pond, spray water quality regulator according to abnormal parameters of abnormal areas in the breeding pond to regulate water quality, and the abnormal warning module is used to remind the breeder through the user terminal when the water quality of the breeding pond is abnormal. The data acquisition module, water quality management module and water quality regulation module are connected to each other for communication; The water quality management module includes a water quality detection module, which is used to detect water quality parameters in the breeding pond in real time, analyze whether the water quality parameters are abnormal, and further analyze the mutual influence between abnormal parameters; The water quality detection module includes a water quality parameter detection submodule, an abnormal parameter analysis submodule and a parameter prediction submodule. The water quality parameter detection submodule is used to detect in real time whether the water quality parameters of each area in the breeding pond are abnormal. The abnormal parameter analysis submodule is used to analyze the mutual influence between the abnormal parameters. The parameter prediction submodule is used to train a model based on the mutual influence relationship between the abnormal parameters, and use the model to predict the changes in the water quality parameters in the breeding pond; The water quality management module also includes an equipment control module, which is used to analyze the abnormal degree of water quality abnormal parameters in each area, calculate the preparation concentration of water quality regulator, feeding speed and operating power of oxygenating equipment according to the abnormal degree, and adjust the equipment to improve the water quality of the breeding pond according to the calculation results; The equipment control module includes a dosage analysis submodule, an equipment power calculation submodule and an equipment regulation submodule. The dosage analysis submodule is used to analyze the parameter changes of water quality and calculate the dosage of feed and water quality regulator according to the analysis results. The equipment power calculation submodule is used to analyze the dissolved oxygen content in each area of ​​the breeding pond and calculate the operating power of the oxygenation equipment according to the analysis results. The equipment regulation submodule is used to mark the area where the water quality parameters are abnormal, and control the water quality regulator spraying speed of the UAV according to the impact degree and location of the abnormal area.

2. A water quality measurement and control system for fishery aquaculture according to claim 1, characterized in that: The data acquisition module includes a sensor module, a comprehensive information entry module for aquaculture ponds and a historical processing data entry module. The sensor module is used to collect comprehensive water quality detection data of the aquaculture pond in real time. The comprehensive information entry module for aquaculture ponds is used to enter comprehensive information of the aquaculture ponds into the system. The historical processing data entry module is used to enter abnormal water quality data of the aquaculture ponds into the system.

3. A water quality measurement and control system for fishery breeding according to claim 2, characterized in that: The abnormal warning module includes a communication module and an early warning module. The communication module is used to communicate with the user end, and the early warning module is used to issue an alarm when the water quality of the breeding pond is abnormal.

4. A water quality measurement and control system for fishery breeding according to claim 3, characterized in that: The operation method of the water quality measurement and control system mainly comprises the following steps: Step S1: Collect the comprehensive water quality detection data of each area of ​​the breeding pond in real time through the sensor module, enter the comprehensive information of the breeding pond into the system through the breeding pond comprehensive information input module, and enter the abnormal water quality of the breeding pond into the system through the historical processing data input module; Step S2: After the data collection is completed, the system starts the water quality detection module and starts to analyze the water quality parameters of each area of ​​the aquaculture pond. According to the analysis results, the mutual influence between abnormal parameters is further analyzed, and the model is trained according to the analysis results to predict the changes in water quality parameters; Step S3: When regulating the water quality, the system starts the equipment control module, calculates the concentration of the water quality regulator, the feeding speed and the operating power of the oxygenator according to the real-time abnormal parameters and the predicted abnormal parameters, and regulates the equipment according to the calculation results; Step S4: When dispensing the water quality regulator, the system marks the area with abnormal water quality parameters, and calculates the spraying speed of the unmanned sprayer according to the abnormal parameter value of the abnormal area; Step S5: When the water quality parameters in the breeding pond are abnormal, a connection is established with the user end through the communication module, and an alarm is sent to the user end.

5. A water quality measurement and control system for fishery breeding according to claim 4, characterized in that: The step S2 further comprises the following steps: Step S21: Acquire historical processing data of water quality in the aquaculture pond, identify abnormal water quality parameter sets in each area in the historical processing data, identify abnormal parameter combinations and corresponding abnormal parameter features; Step S22: Identify the mutual influence relationship between each abnormal parameter in the water quality abnormal parameter set of each area, construct an abnormal parameter influence knowledge map according to the identified influence relationship, use the abnormal parameter combination, abnormal parameter characteristics and the mutual influence relationship between the abnormal parameters as sample data, retrieve the corresponding water quality parameter prediction model in the database, train the water quality parameter prediction model, and use the water quality parameter prediction model to predict the water quality parameters of each area of ​​the aquaculture pond; Step S23: Obtain the sensor data of the breeding pond, identify the water quality parameters of each area of ​​the breeding pond, identify the actual stamps of the water quality parameters and the corresponding values, establish a coordinate system, mark the water quality parameters in the coordinate system, connect the water quality parameter points in sequence, construct a water quality parameter change line graph, identify the change characteristics of the water quality parameter change line graph, and predict the water quality parameters of each area of ​​the breeding pond according to the change characteristics; Step S24: Calculate the difference between the water quality parameters predicted by the prediction model. When the difference is less than the minimum threshold, select the average of the two as the prediction value. When the difference is greater than the minimum threshold and less than the maximum threshold, perform weighted fusion on the two prediction values ​​and select the weighted fusion value as the prediction value. When the difference is greater than the maximum threshold, identify the relationship between the parameters in the prediction parameter set, and compare the database based on the relationship between the parameters. If the matching degree is less than the threshold, delete the prediction value. Otherwise, select the prediction parameter as the prediction value.

6. A water quality measurement and control system for fishery farming according to claim 5, characterized in that: The step S3 further comprises the following steps: Step S31: Obtain the predicted values ​​of water quality parameters, identify the predicted values ​​of dissolved oxygen, pH value and ammonia nitrogen concentration in the data, retrieve the corresponding water quality parameter standards in the database, compare the predicted value of pH value with the water quality parameter standards, if the predicted value of pH value is greater than the minimum value and less than the maximum value, then retrieve the corresponding parameter standard influence coefficient α in the database according to the difference between the predicted value of pH value and the optimal value of pH, otherwise the system continues to detect; Step S32: Identify the predicted oxygen capacity value m of the target area in the aquaculture pond, and calculate the difference between the predicted oxygen capacity value and the parameter standard by the formula Q=m-α M, where Q represents the difference between the predicted oxygen capacity value and the parameter standard, and M represents the parameter standard value. If the difference is less than the threshold, it is marked as an abnormal parameter, otherwise the system continues to detect; Step S33: Identify abnormal parameters, retrieve the oxygen capacity parameter change line graph in the corresponding period in the database, identify the change characteristics of oxygen capacity in the line graph, if the change characteristic is growth, retrieve the corresponding growth rate in the database according to the change characteristic, otherwise retrieve the corresponding reduction rate in the database, and calculate the time required for oxygen capacity to grow to the parameter standard through the formula = , where Indicates the time required for oxygen capacity to increase to the parameter standard. Indicates the growth rate of the target area of ​​the aquaculture pond. When the oxygen capacity is less than the threshold set by the system, the oxygen supply speed of the oxygen supply equipment required within the set time is calculated by the formula = + , where Indicates the oxygen supply speed of the oxygen supply equipment required for the oxygen capacity within the set time. Indicates the oxygen supply time set by the system. Indicates the growth rate of the target area of ​​the aquaculture pond. According to the calculated oxygenation speed of the required oxygenation equipment, the corresponding equipment operating power is retrieved from the database, and the equipment is started for oxygenation according to the equipment operating power. Otherwise, the system continues to detect.

7. A water quality measurement and control system for fishery farming according to claim 6, characterized in that: In step S33, the predicted value of the ammonia nitrogen concentration in the breeding pond is obtained and compared with the database. When the ammonia nitrogen concentration is greater than the system set threshold, the oxygen capacity of the breeding pond is detected. If the oxygen capacity is consistent with the parameter standard, the corresponding feed reduction amount in the database is retrieved according to the difference between the ammonia nitrogen concentration and the parameter standard, and the feed amount is reduced. Otherwise, the oxygen supply equipment is started to compensate the oxygen in the breeding pond.

8. A water quality measurement and control system for fishery farming according to claim 7, characterized in that: In step S4, the abnormal water quality parameter H of each area in the aquaculture pond is identified, and the average value of the abnormal water quality parameter is calculated by the formula According to the average of water quality parameters, the corresponding water quality regulator concentration in the database is retrieved, and the water quality abnormal parameter deviation coefficient is calculated by the formula , where P represents the water quality abnormal parameter deviation coefficient, j=1,2,3.....n, and the corresponding influence coefficient β on the speed of the unmanned sprayer is retrieved from the database according to the water quality abnormal parameter deviation coefficient, and the speed of the unmanned sprayer over the target area is calculated by the formula =β , where Indicates the speed of the unmanned sprayer over the target area. It indicates the rated speed of the unmanned sprayer. According to the flight speed of the unmanned sprayer, the best spraying route is planned for the unmanned sprayer to spray the water quality regulator on the target area.

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