A water quality measurement and control system for fishery aquaculture

Abstract

The present invention discloses a water quality measurement and control system for fishery aquaculture, including 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 the water quality in the aquaculture pond, input the comprehensive information and historical processing data of the aquaculture pond into the system, the water quality management module is used to analyze the abnormal parameters of the water quality, further analyze the mutual influence between the abnormal parameters of the water quality, determine the primary and secondary relationships of the abnormal parameters according to the analysis results, calculate the concentration and dosage of the water quality regulator according to the abnormal parameters, calculate the operating power of the oxygenation equipment, mark the abnormal areas in the aquaculture pond, and spray the water quality regulator on the water quality according to the abnormal parameters of the abnormal areas in the aquaculture pond to regulate the water quality, and the abnormal warning module is used to remind the aquaculture farmers through the user terminal when the water quality in the aquaculture pond is abnormal. The present invention has the characteristics of high accuracy and high efficiency.

Description

Technical Field

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

[0002] With the rapid development of Internet technology, fishery culture in China has started to use scientific and technological achievements to improve the water quality of aquaculture, making the water quality more conducive to the growth of fish, so as to achieve the purpose of increasing production.

[0003] At present, most fishery farmers still use simple detection equipment combined with aquaculture experience to judge the changes in water quality, and then improve the water quality according to experience. However, due to the mutual influence of abnormal water quality in aquaculture, 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 of water quality parameter regulation. Moreover, most farmers analyze water quality problems manually, calculate the dosage of regulators, and sprinkle agents, resulting in low treatment efficiency and poor accuracy. Therefore, it is necessary to design a water quality measurement and control system for fishery culture with high accuracy and high efficiency. Summary of the Invention

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

[0005] To solve the above technical problems, the present invention provides the following technical solution: A water quality measurement and control system for fishery culture, including 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 the water quality in the aquaculture pond, and input the comprehensive information and historical processing data of the aquaculture pond into the system; the water quality management module is used to analyze the abnormal parameters of the water quality, further analyze the mutual influence between the abnormal water quality parameters, determine the primary and secondary relationships of the abnormal parameters according to the analysis results, calculate the concentration and dosage of the water quality regulator according to the abnormal parameters, calculate the feeding speed and feeding amount of the feeding equipment, calculate the operating power of the oxygenation equipment, mark the abnormal areas in the aquaculture pond, and spray the water quality regulator according to the abnormal parameters in the abnormal areas in the aquaculture pond to regulate the water quality; the abnormal warning module is used to remind the farmer through the user terminal when the water quality in the aquaculture pond is abnormal; the data acquisition module, the water quality management module, and the water quality regulation module are communicatively connected to each other;

[0006] The water quality detection module includes a water quality parameter detection sub-module, an abnormal parameter analysis sub-module, and a parameter prediction sub-module. The water quality parameter detection sub-module is used to detect in real time whether the water quality parameters in each area of the aquaculture pond are abnormal. The abnormal parameter analysis sub-module is used to analyze the mutual influence between abnormal parameters. The parameter prediction sub-module is used to train a model based on the mutual influence relationship between abnormal parameters and use the model to predict the change of water quality parameters in the aquaculture pond;

[0007] The equipment control module includes a dosing analysis sub-module, an equipment power calculation sub-module, and an equipment regulation sub-module. The dosing analysis sub-module is used to analyze the parameter changes of the water quality, calculate the dosing amounts of feed and water quality regulators according to the analysis results. The equipment power calculation sub-module is used to analyze the dissolved oxygen content in each area of the aquaculture pond and calculate the operating power of the oxygenation equipment according to the analysis results. The equipment regulation sub-module is used to mark the areas where water quality parameters are abnormal, and control the spraying speed of the water quality regulator of the drone according to the influence degree and position of the abnormal areas.

[0008] According to the above technical solution, the data acquisition module includes a sensor module, an aquaculture pond comprehensive information input module, and a historical processed data input module. The sensor module is used to collect in real time the comprehensive water quality detection data of the aquaculture pond. The aquaculture pond comprehensive information input module is used to input the comprehensive information of the aquaculture pond into the system. The historical processed data input module is used to input the historical processed data of water quality abnormalities in the aquaculture pond into the system.

[0009] According to the above technical solution, the water quality management module includes a water quality detection module. The water quality detection module is used to detect in real time the water quality parameters in the aquaculture pond, analyze whether the water quality parameters are abnormal, and further analyze the mutual influence between abnormal parameters.

[0010] According to the above technical solution, the water quality management module further includes an equipment control module. The equipment control module is used to analyze the abnormality 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 abnormality degree, and regulate the equipment according to the calculation results to improve the water quality of the aquaculture pond.

[0011] 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 terminal. The warning module is used to issue an alarm when the water quality in the aquaculture pond is abnormal.

[0012] According to the above technical solution, the operation method of the water quality measurement and control system includes the following steps:

[0013] Step S1: Through the sensor module, collect the comprehensive water quality detection data of each area of the aquaculture pond in real time. Through the aquaculture pond comprehensive information input module, input the comprehensive information of the aquaculture pond into the system. Through the historical processed data input module, input the historical processed data of water quality anomalies in the aquaculture pond into the system;

[0014] Step S2: After the data collection is completed, the system starts the water quality detection module, begins to analyze the water quality parameters of each area of the aquaculture pond, further analyzes the mutual influence between abnormal parameters according to the analysis results, trains a model according to the analysis results, and predicts the changes of water quality parameters;

[0015] Step S3: When regulating the water quality, the system starts the equipment control module, calculates the preparation concentration of the water quality regulator, the feeding speed, and the operating power of the aerator according to the real-time abnormal parameters and the predicted abnormal parameters, and regulates the equipment according to the calculation results;

[0016] Step S4: When preparing the water quality regulator, the system marks the areas with abnormal water quality parameters, and calculates the spraying speed of the unmanned spraying machine according to the abnormal parameter values of the abnormal areas;

[0017] Step S5: When the water quality parameters in the aquaculture pond are abnormal, establish a connection with the user terminal through the communication module and send an alarm to the user terminal.

[0018] According to the above technical solution, step S2 further includes the following steps:

[0019] Step S21: Obtain the historical processed data of the aquaculture pond water quality, identify the water quality abnormal parameter sets of each area in the historical processed data, and identify the abnormal parameter combinations and the corresponding abnormal parameter characteristics;

[0020] Step S22: Identify the mutual influence relationships between the abnormal parameters in each area's water quality abnormal parameter set, construct an abnormal parameter influence knowledge graph according to the identified influence relationships, use the abnormal parameter combinations, abnormal parameter characteristics, and the mutual influence relationships 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;

[0021] Step S23: Obtain the aquaculture pond sensor data, identify the water quality parameters of each area of the aquaculture pond, identify the actual timestamps and corresponding values of the water quality parameters, establish a coordinate system, mark the water quality parameters in the coordinate system, connect the water quality parameter points in sequence to 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 aquaculture pond according to the change characteristics;

[0022] Step S24: Calculate the difference between the predicted water quality parameters by the prediction model. When the difference is less than the minimum threshold, the average value of the two is selected as the predicted value. When the difference is greater than the minimum threshold and less than the maximum threshold, the two predicted values are weighted and fused, and the weighted and fused value is selected as the predicted value. When the difference is greater than the maximum threshold, identify the relationships between the parameters in the predicted parameter set, compare with the database according to the relationships between the parameters. If the matching degree is less than the threshold, delete the predicted water quality parameters, otherwise select the predicted water quality parameters as the predicted value.

[0023] According to the above technical solution, step S3 further includes the following steps:

[0024] 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, and compare the predicted value of the pH value with the water quality parameter standards. If the predicted value of the 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 the pH value and the optimal pH value, otherwise the system continues to detect;

[0025] Step S32: Identify the predicted value m of the oxygen capacity in the target area of the aquaculture pond. Calculate the difference Q = m - α·M between the predicted value of the oxygen capacity and the parameter standard through the formula, where Q represents the difference between the predicted value of the oxygen capacity 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;

[0026] Step S33: Identify the abnormal parameter, retrieve the oxygen capacity parameter change line chart in the corresponding period in the database, identify the change characteristics of the oxygen capacity in the line chart. If the change characteristic is an increase, retrieve the corresponding growth rate in the database according to the change characteristic, otherwise retrieve the corresponding decrease rate in the database, and calculate the time required for the oxygen capacity to grow to the parameter standard through the formula In the formula, T1 represents the time required for the oxygen capacity to grow to the parameter standard, and ν1 represents the growth rate of the target area of the aquaculture pond. When T1 is less than the system - set threshold, calculate the oxygenation speed of the oxygenation equipment required for the oxygen capacity within the set time through the formula In the formula, ν3 represents the oxygenation speed of the oxygenation equipment required for the oxygen capacity within the set time, T0 represents the system - set oxygenation time, and ν2 represents the growth rate of the target area of the aquaculture pond. According to the calculated oxygenation speed of the required oxygenation equipment, retrieve the corresponding equipment operating power in the database, and start the equipment for oxygenation according to the equipment operating power, otherwise the system continues to detect.

[0027] According to the above technical solution, in step S33, the predicted value of the ammonia nitrogen concentration in the aquaculture pond is obtained. In the comparison database, when the ammonia nitrogen concentration is greater than the system-set threshold, the oxygen capacity of the aquaculture 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 oxygenation equipment is started to compensate the oxygen in the aquaculture pond.

[0028] According to the above technical solution, in step S4, the water quality abnormal parameter H in each area of the aquaculture pond is identified, and the average value of the water quality abnormal parameter is calculated by a formula. According to the average value of the water quality parameters, the corresponding water quality regulator concentration in the database is retrieved, and the deviation coefficient of the water quality abnormal parameter is calculated by a formula. In the formula, P represents the deviation coefficient of the water quality abnormal parameter, j = 1, 2, 3......n. According to the deviation coefficient of the water quality abnormal parameter, the influence coefficient β on the driving speed of the unmanned spraying machine in the database is retrieved, and the driving speed ν4 of the unmanned spraying machine over the target area is calculated by the formula ν4 = β·ν0. In the formula, ν4 represents the driving speed of the unmanned spraying machine over the target area, and ν0 represents the rated driving speed of the unmanned spraying machine. According to the flying speed of the unmanned spraying machine, the best spraying route is planned for the unmanned spraying machine, and the water quality regulator is sprayed on the target area.

[0029] Compared with the prior art, the beneficial effects achieved by the present invention are as follows: By comparing the difference between the model predicted value and the trend predicted value and correcting the predicted parameter value, the deviation of the water quality parameter predicted value can be reduced, 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 aquaculture pond, reducing the water quality regulation time, avoiding the impact of water quality changes on the aquaculture objects, thereby reducing losses and improving efficiency. By analyzing the influence of the PH value in the water quality parameters on the water quality parameter standard, the water quality can be accurately regulated to make it more suitable for the growth of the aquaculture objects, thereby greatly improving the accuracy of the system. By analyzing the change trend of the oxygen capacity in the target area, and then calculating the required oxygenation speed, and setting the power of the oxygenation equipment according to the oxygenation speed, it can ensure that the oxygenation equipment can quickly and accurately supplement oxygen to the target area, further improving the accuracy and efficiency of the system. By analyzing the ammonia nitrogen content in the aquaculture pond and then reducing the feeding amount, it can avoid overfeeding, resulting in abnormal water quality parameters, thereby reducing the aquaculture cost and avoiding water quality abnormalities. By adjusting the driving speed of the unmanned spraying machine, it can ensure that the driving speed is slower in the target area with serious abnormal water quality parameters, ensuring the accurate dosage of the sprayed regulator. BRIEF DESCRIPTION OF THE DRAWINGS

[0030] The drawings are used to provide a further understanding of the present invention, and constitute a part of the specification. They are used together with the embodiments of the present invention to explain the present invention, and do not constitute a limitation to the present invention. In the drawings:

[0031] Figure 1 It is a schematic diagram of the system module composition of the present invention. Specific implementation manners

[0032] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without making creative efforts shall fall within the protection scope of the present invention.

[0033] Please refer to Figure 1 , the present invention provides a technical solution: a water quality measurement and control system for fishery aquaculture, including 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 the water quality in the aquaculture pond, input the comprehensive information and historical processing data of the aquaculture pond into the system, the water quality management module is used to analyze the abnormal parameters of the water quality, further analyze the mutual influence between the abnormal water quality parameters, determine the primary and secondary relationships of the abnormal parameters according to the analysis results, calculate the concentration and dosage of the water quality regulator according to the abnormal parameters, calculate the feeding speed and feeding amount of the feeding equipment, calculate the operating power of the oxygenation equipment, mark the abnormal areas in the aquaculture pond, spray the water quality regulator according to the abnormal parameters in the abnormal areas in the aquaculture pond to regulate the water quality, the abnormal warning module is used to remind the aquaculture farmers through the user terminal when the water quality in the aquaculture pond is abnormal, and the data acquisition module, the water quality management module, and the water quality regulation module are communicatively connected to each other;

[0034] The water quality detection module includes a water quality parameter detection sub-module, an abnormal parameter analysis sub-module, and a parameter prediction sub-module. The water quality parameter detection sub-module is used to detect in real time whether the water quality parameters in each area of the aquaculture pond are abnormal. The abnormal parameter analysis sub-module is used to analyze the mutual influence between the abnormal parameters. The parameter prediction sub-module is used to train a model according to the mutual influence relationship between the abnormal parameters and use the model to predict the change of the water quality parameters in the aquaculture pond;

[0035] The equipment control module includes a dosing analysis sub-module, an equipment power calculation sub-module, and an equipment regulation sub-module. The dosing analysis sub-module is used to analyze the parameter changes of the water quality and calculate the dosages of the feed and the water quality regulator according to the analysis results. The equipment power calculation sub-module is used to analyze the dissolved oxygen content in each area of the aquaculture pond and calculate the operating power of the oxygenation equipment according to the analysis results. The equipment regulation sub-module is used to mark the areas where the water quality parameters are abnormal and control the spraying speed of the water quality regulator of the drone according to the influence degree and position of the abnormal areas.

[0036] The data acquisition module includes a sensor module, a comprehensive information input module for aquaculture ponds, and a historical processed data input module. The sensor module is used to collect real-time comprehensive water quality detection data of aquaculture ponds. The comprehensive information input module for aquaculture ponds is used to input the comprehensive information of aquaculture ponds into the system. The historical processed data input module for water quality anomalies in aquaculture ponds is used to input the historical processed data of water quality anomalies in aquaculture ponds into the system.

[0037] The water quality management module includes a water quality detection module. The water quality detection module is used to detect the water quality parameters in aquaculture ponds in real time, analyze whether the water quality parameters are abnormal, and further analyze the mutual influence between abnormal parameters.

[0038] The water quality management module also includes an equipment control module. The equipment control module is used to analyze the degree of abnormality of water quality abnormal parameters in each area, calculate the preparation concentration of water quality regulators, feeding speed, and operating power of oxygenation equipment according to the degree of abnormality, and regulate the equipment according to the calculation results to improve the water quality of aquaculture ponds.

[0039] The abnormal warning module includes a communication module and a warning module. The communication module is used to communicate with the user terminal. The warning module is used to issue an alarm when the water quality of the aquaculture pond is abnormal.

[0040] The operation method of the water quality measurement and control system includes the following steps:

[0041] Step S1: Through the sensor module, collect real-time comprehensive water quality detection data of each area of the aquaculture pond. Through the comprehensive information input module for aquaculture ponds, input the comprehensive information of the aquaculture pond into the system. Through the historical processed data input module for water quality anomalies in aquaculture ponds, input the historical processed data of water quality anomalies in the aquaculture pond into the system;

[0042] Step S2: After the data collection is completed, the system starts the water quality detection module, begins to analyze the water quality parameters of each area of the aquaculture pond, further analyzes the mutual influence between abnormal parameters according to the analysis results, and trains a model according to the analysis results to predict the change of water quality parameters;

[0043] Step S3: When regulating the water quality, the system starts the equipment control module, calculates the preparation concentration of water quality regulators, feeding speed, and operating power of the aerator according to the real-time abnormal parameters and predicted abnormal parameters, and regulates the equipment according to the calculation results;

[0044] Step S4: When preparing the water quality regulator, the system marks the area where the water quality parameters are abnormal, and calculates the spraying speed of the unmanned spraying machine according to the abnormal parameter values in the abnormal area;

[0045] Step S5: When the water quality parameters in the aquaculture pond are abnormal, establish a connection with the user terminal through the communication module and issue an alarm to the user terminal.

[0046] Step S2 further includes the following steps:

[0047] Step S21: Obtain the historical treatment data of the water quality in the aquaculture pond, identify the water quality abnormal parameter sets in each area of the historical treatment data, identify the abnormal parameter combinations and the corresponding abnormal parameter characteristics;

[0048] Step S22: Identify the mutual influence relationships among the abnormal parameters in each water quality abnormal parameter set in each area, construct an abnormal parameter influence knowledge graph according to the identified influence relationships, use the abnormal parameter combinations, abnormal parameter characteristics and the mutual influence relationships among 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 in each area of the aquaculture pond;

[0049] Step S23: Obtain the sensor data of the aquaculture pond, identify the water quality parameters in each area of the aquaculture pond, identify the actual timestamps and the corresponding values of the water quality parameters, establish a coordinate system, mark the water quality parameters in the coordinate system, connect the water quality parameter points in sequence to 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 in each area of the aquaculture pond according to the change characteristics, and by comparing the difference between the model prediction value and the trend prediction value and correcting the predicted parameter value, the deviation of the water quality parameter prediction value can be reduced, thereby greatly improving the accuracy of the system;

[0050] Step S24: Calculate the difference between the predicted water quality parameters by the prediction model. When the difference is less than the minimum threshold, the average value of the two is selected as the prediction value. When the difference is greater than the minimum threshold and less than the maximum threshold, the two predicted values are weighted and fused, and the weighted and fused value is selected as the prediction value. When the difference is greater than the maximum threshold, identify the relationships among the parameters in the predicted parameter set, compare the database according to the relationships among the parameters. If the matching degree is less than the threshold, the predicted water quality parameters are deleted, otherwise the predicted water quality parameters are selected as the prediction value. By predicting the water quality parameters, the equipment can be started in advance to adjust the water quality in the aquaculture pond, reduce the water quality regulation time, avoid the impact of water quality changes on the aquaculture, thereby reducing losses and improving efficiency.

[0051] Step S3 further includes the following steps:

[0052] 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 the pH value with the water quality parameter standards. If the predicted value of the pH value is greater than the minimum value and less than the maximum value, then according to the difference between the predicted value of the pH value and the optimal pH value, retrieve the corresponding parameter standard influence coefficient α in the database. Otherwise, the system continues to detect. By analyzing the influence of the pH value in the water quality parameters on the water quality parameter standards, the water quality can be accurately regulated to make it more suitable for the growth of the cultured organisms, thereby greatly improving the accuracy of the system;

[0053] Step S32: Identify the predicted value m of the oxygen capacity in the target area of the aquaculture pond. Calculate the difference Q = m - α·M between the predicted value of the oxygen capacity and the parameter standard through the formula, where Q represents the difference between the predicted value of the oxygen capacity 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;

[0054] Step S33: Identify the abnormal parameters, retrieve the line graph of the change in oxygen capacity parameters in the corresponding period in the database, and identify the change characteristics of the oxygen capacity in the line graph. If the change characteristic is an increase, then retrieve the corresponding growth rate in the database according to the change characteristic. Otherwise, retrieve the corresponding decrease rate in the database. Calculate the time required for the oxygen capacity to increase to the parameter standard through the formula In the formula, T1 represents the time required for the oxygen capacity to increase to the parameter standard, and ν1 represents the growth rate of the target area of the aquaculture pond. When T1 is less than the system - set threshold, then calculate the oxygen - supply speed of the oxygen - supply equipment required for the oxygen capacity within the set time through the formula In the formula, ν3 represents the oxygen - supply speed of the oxygen - supply equipment required for the oxygen capacity within the set time, T0 represents the system - set oxygen - supply time, and ν2 represents the growth rate of the target area of the aquaculture pond. According to the calculated oxygen - supply speed of the required oxygen - supply equipment, retrieve the corresponding equipment operation power in the database, and start the equipment for oxygen supply according to the equipment operation power. Otherwise, the system continues to detect. By analyzing the change trend of the oxygen capacity in the target area, and then calculating the required oxygen - supply speed, and setting the power of the oxygen - supply equipment according to the oxygen - supply speed, it can ensure that the oxygen - supply equipment can quickly and accurately supplement oxygen to the target area, further improving the accuracy and efficiency of the system.

[0055] Obtain the predicted value of the ammonia nitrogen concentration in the aquaculture pond in Step S33. Compare it in the database. When the ammonia nitrogen concentration is greater than the system - set threshold, then detect the oxygen capacity of the aquaculture pond. If the oxygen capacity is consistent with the parameter standard, then according to the difference between the ammonia nitrogen concentration and the parameter standard, retrieve the corresponding amount of reduced feeding in the database and reduce the feeding amount. Otherwise, start the oxygen - supply equipment to compensate the oxygen in the aquaculture pond. By analyzing the ammonia nitrogen content in the aquaculture pond and then reducing the feeding amount, it can avoid over - feeding, resulting in abnormal water quality parameters, thereby reducing the breeding cost and avoiding water quality anomalies.

[0056] In step S4, identify the water quality abnormal parameter H in each area of the aquaculture pond, and calculate the average value of the water quality abnormal parameter through the formula. Retrieve the corresponding water quality regulator concentration in the database according to the average value of the water quality parameters, and calculate the deviation coefficient of the water quality abnormal parameter through the formula. In the formula, P represents the deviation coefficient of the water quality abnormal parameter, j = 1, 2, 3......n. Retrieve the corresponding influence coefficient β on the driving speed of the unmanned spraying machine in the database according to the deviation coefficient of the water quality abnormal parameter, and calculate the driving speed ν4 of the unmanned spraying machine over the target area through the formula ν4 = β·ν0. In the formula, ν4 represents the driving speed of the unmanned spraying machine over the target area, and ν0 represents the rated driving speed of the unmanned spraying machine. Plan the optimal spraying route for the unmanned spraying machine according to the flying speed of the unmanned spraying machine, and spray the water quality regulator on the target area. By adjusting the driving speed of the unmanned spraying machine, it is possible to ensure that the driving speed is slower in the target area where the water quality parameters are abnormally severe, and ensure that the accurate dosage of the regulator is sprayed.

[0057] It should be noted that in this article, relational terms such as first and second are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any actual relationship or order between these entities or operations. Moreover, the term "including", "comprising" or any other variant thereof is intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements not only includes those elements, but also includes other elements not expressly listed, or also includes elements inherent to such process, method, article or device.

[0058] Finally, it should be noted that the above are only the preferred embodiments of the present invention and are not used to limit the present invention. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art can still modify the technical solutions described in the foregoing embodiments, or perform equivalent replacements for some of the technical features. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principle of the present invention shall be included within 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 the water quality in the aquaculture pond, and input the comprehensive information and historical processing data of the aquaculture pond into the system. The water quality management module is used to analyze the abnormal parameters of the water quality, further analyze the mutual influence between the abnormal water quality parameters, determine the primary and secondary relationships of the abnormal parameters according to the analysis results, calculate the concentration and dosage of the water quality regulator according to the abnormal parameters, calculate the feeding speed and feeding amount of the feeding equipment, calculate the operating power of the oxygenation equipment, mark the abnormal areas in the aquaculture pond, and spray the water quality regulator according to the abnormal parameters in the abnormal areas in the aquaculture pond to regulate the water quality. The abnormal warning module is used to remind the aquaculture farmers through the user terminal when the water quality in the aquaculture pond is abnormal. The data acquisition module, the water quality management module and the water quality regulation module are communicatively connected to each other; The water quality management module includes a water quality detection module and an equipment control module; The water quality detection module includes a water quality parameter detection sub-module, an abnormal parameter analysis sub-module and a parameter prediction sub-module. The water quality parameter detection sub-module is used to detect in real time whether the water quality parameters in each area of the aquaculture pond are abnormal. The abnormal parameter analysis sub-module is used to analyze the mutual influence between the abnormal parameters. The parameter prediction sub-module is used to train a model according to the mutual influence relationship between the abnormal parameters and use the model to predict the change of the water quality parameters in the aquaculture pond; The equipment control module includes a dosing analysis sub-module, an equipment power calculation sub-module and an equipment regulation sub-module. The dosing analysis sub-module is used to analyze the parameter changes of the water quality and calculate the dosing amounts of the feed and the water quality regulator according to the analysis results. The equipment power calculation sub-module is used to analyze the dissolved oxygen content in each area of the aquaculture pond and calculate the operating power of the oxygenation equipment according to the analysis results. The equipment regulation sub-module is used to mark the areas where the water quality parameters are abnormal and control the spraying speed of the water quality regulator of the unmanned aerial vehicle according to the influence degree and position of the abnormal areas.

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

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

4. The water quality measurement and control system for fishery aquaculture according to claim 3, characterized in that: The operation method of the water quality measurement and control system includes the following steps: Step S1: Through the sensor module, collect comprehensive detection data of the water quality in each area of the aquaculture pond in real time. Through the aquaculture pond comprehensive information input module, input the comprehensive information of the aquaculture pond into the system. Through the historical processing data input module, input the historical processing data of the water quality abnormality in the aquaculture pond into the system; Step S2: After the data collection is completed, the system starts the water quality detection module, begins to analyze the water quality parameters in each area of the aquaculture pond, further analyzes the mutual influence between the abnormal parameters according to the analysis results, trains a model according to the analysis results, and predicts the change of the water quality parameters; Step S3: When regulating the water quality, the system starts the equipment control module, calculates the preparation concentration of the water quality regulator, the feeding speed, and the operating power of the aerator according to the real-time abnormal parameters and the predicted abnormal parameters, and regulates the equipment according to the calculation results; Step S4: When preparing the water quality regulator, the system marks the areas with abnormal water quality parameters, and calculates the spraying speed of the unmanned spraying machine according to the abnormal parameter values of the abnormal areas; Step S5: When the water quality parameters in the aquaculture pond are abnormal, establish a connection with the user terminal through the communication module and send an alarm to the user terminal.

5. The water quality measurement and control system for fishery farming according to claim 4, characterized in that: The said Step S2 further includes the following steps: Step S21: Obtain the historical treatment data of the aquaculture pond water quality, identify the water quality abnormal parameter sets of each area in the historical treatment data, and identify the abnormal parameter combinations and the corresponding abnormal parameter characteristics; Step S22: Identify the mutual influence relationships between the abnormal parameters in each water quality abnormal parameter set of each area, construct a knowledge graph of the influence of abnormal parameters according to the identified influence relationships, use the abnormal parameter combinations, abnormal parameter characteristics, and the mutual influence relationships 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 aquaculture pond, identify the water quality parameters of each area of the aquaculture pond, identify the actual timestamps and the corresponding values of the water quality parameters, establish a coordinate system, mark the water quality parameters in the coordinate system, connect the water quality parameter points in sequence to construct a line graph of the change of water quality parameters, identify the change characteristics of the line graph of the change of water quality parameters, and predict the water quality parameters of each area of the aquaculture 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, then select the average value of the two as the predicted value. When the difference is greater than the minimum threshold and less than the maximum threshold, then perform weighted fusion on the two predicted values and select the weighted fusion value as the predicted value. When the difference is greater than the maximum threshold, then identify the relationships between the parameters in the predicted parameter set, compare with the database according to the relationships between the parameters. If the matching degree is less than the threshold, then delete the predicted water quality parameters, otherwise select the predicted water quality parameters as the predicted value.

6. The water quality measurement and control system for fishery aquaculture according to claim 5, characterized in that: The said 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 the pH value with the water quality parameter standards. If the predicted value of the pH value is greater than the minimum value and less than the maximum value, then according to the difference between the predicted value of the pH value and the optimal pH value, retrieve the corresponding parameter standard influence coefficient α in the database, otherwise the system continues to detect; Step S32: Identify the predicted value m of the oxygen capacity in the target area of the aquaculture pond, calculate the difference Q = m - α·M between the predicted value of the oxygen capacity and the parameter standard through the formula, where Q represents the difference between the predicted value of the oxygen capacity and the parameter standard, and M represents the parameter standard value. If the difference is less than the threshold, then mark it as an abnormal parameter, otherwise the system continues to detect; Step S33: Identify abnormal parameters, retrieve the line chart of the change in oxygen capacity parameters for the corresponding period in the database, identify the change characteristics of the oxygen capacity in the line chart. If the change characteristic is an increase, retrieve the corresponding growth rate in the database according to the change characteristic; otherwise, retrieve the corresponding decrease rate in the database. Calculate the time required for the oxygen capacity to increase to the parameter standard through the formula In the formula, T1 represents the time required for the oxygen capacity to increase to the parameter standard, and ν1 represents the growth rate of the target area of the aquaculture pond. When T1 is less than the system-set threshold, calculate the oxygenation rate of the oxygenation equipment required for the oxygen capacity within the set time through the formula In the formula, ν3 represents the oxygenation rate of the oxygenation equipment required for the oxygen capacity within the set time, T0 represents the system-set oxygenation time, and ν2 represents the growth rate of the target area of the aquaculture pond. According to the calculated oxygenation rate of the required oxygenation equipment, retrieve the corresponding equipment operating power in the database, and start the equipment for oxygenation according to the equipment operating power; otherwise, the system continues to detect.

7. The water quality measurement and control system for fishery aquaculture according to claim 6, characterized in that: In step S33, obtain the predicted value of the ammonia nitrogen concentration in the aquaculture pond. In the database comparison, when the ammonia nitrogen concentration is greater than the system-set threshold, detect the oxygen capacity of the aquaculture pond. If the oxygen capacity is consistent with the parameter standard, then according to the difference between the ammonia nitrogen concentration and the parameter standard, retrieve the corresponding feed reduction amount in the database and reduce the feed intake. Otherwise, start the oxygenation equipment to compensate for the oxygen in the aquaculture pond.

8. A water quality measurement and control system for fishery aquaculture according to claim 7, characterized in that: In step S4, the water quality anomaly parameter H in each area of the aquaculture pond is identified, the average value H of the water quality anomaly parameter is calculated by a formula, the corresponding water quality regulator concentration in the database is retrieved according to the average value of the water quality parameters, and the deviation coefficient of the water quality anomaly parameter is calculated by a formula In the formula, P represents the deviation coefficient of the water quality anomaly parameter, j = 1, 2, 3......n. According to the deviation coefficient of the water quality anomaly parameter, the influence coefficient β on the driving speed of the unmanned spraying machine is retrieved from the database, and the driving speed ν4 of the unmanned spraying machine over the target area is calculated by the formula ν4 = β·ν0. In the formula, ν4 represents the driving speed of the unmanned spraying machine over the target area, and ν0 represents the rated driving speed of the unmanned spraying machine. According to the flying speed of the unmanned spraying machine, the best spraying route is planned for the unmanned spraying machine, and the water quality regulator is sprayed on the target area

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