A compound disinfection and disinfection by-product control device and method for mandarin fish breeding

Abstract

This invention discloses a device and method for combined disinfection and disinfection byproduct control in mandarin fish farming, belonging to the field of aquaculture recirculating water disinfection technology. It includes a multi-dimensional monitoring unit for constructing a dual monitoring network for water quality and pathogens, a multi-level dynamic disinfection decision-making unit with a built-in BP neural network model, a combined disinfection execution unit for performing corresponding disinfection operations, a byproduct monitoring and removal unit for monitoring and targeted removal of disinfection byproducts, and a PLC intelligent control unit for achieving closed-loop linkage control throughout the entire process. This invention utilizes the aforementioned device and method for combined disinfection and disinfection byproduct control in mandarin fish farming to construct a multi-factor linkage disinfection decision-making model, replacing the traditional "fixed dosage" mode, and achieving precise matching of "contamination level - pathogen type - disinfection scheme".

Description

Technical Field

[0001] This invention relates to the field of aquaculture recirculating water disinfection technology, and in particular to a compound disinfection and disinfection by-product control device and method for mandarin fish farming. Background Technology

[0002] Factory-style recirculating aquaculture is the core model for high-density mandarin fish farming, with a stocking density typically ≥50 fish / m³. 3 In this model, the circulating water is prone to the growth of highly pathogenic microorganisms in mandarin fish, such as Aeromonas hydrophila and Flavobacterium columnare, which can easily trigger outbreaks of diseases such as gill rot and enteritis, causing losses in aquaculture. Therefore, water disinfection is the core link in disease control during factory-scale mandarin fish farming.

[0003] In existing technologies, disinfection of recirculating aquaculture systems for mandarin fish often employs a single disinfection method, such as ultraviolet disinfection, ozone disinfection, or water electrolysis. However, this approach has the following significant drawbacks in practical applications: Firstly, the disinfection methods are simplistic and the dosage control is haphazard. Only a single disinfection method with a fixed dosage is used, without dynamically adjusting the disinfection plan based on water quality parameters such as turbidity and COD and pathogen concentration. This easily leads to problems such as excessive dosage causing chemical irritation to mandarin fish under low pollution conditions and insufficient dosage leading to disinfection failure under high pollution conditions. Secondly, there is a lack of targeted control measures for disinfection byproducts. Ozone disinfection in bromine-containing water bodies easily generates highly toxic byproducts such as bromate. The tolerance threshold of mandarin fish to bromate is only ≤0.01mg / L. Electrolyzed water disinfection easily leaves residual chlorine. A residual chlorine concentration ≥0.1mg / L can cause damage to the gills of mandarin fish. Existing technologies cannot monitor and target the removal of these byproducts in real time, posing a serious risk to aquaculture safety. Third, the technology has not been adapted to the different stages of mandarin fish farming. Mandarin fish are extremely sensitive to chemical stimulation during the fry stage. The existing technology does not distinguish between the disinfection dosage during the fry stage and the adult stage, and adopts a one-size-fits-all disinfection mode, resulting in a low survival rate of mandarin fish during the fry stage. Fourth, the disinfection and monitoring processes are disconnected, a closed-loop control system has not been established, and the disinfection plan cannot be adjusted in real time according to the disinfection effect, which easily leads to over-disinfection or under-disinfection, resulting in poor disinfection stability and reliability.

[0004] Existing composite disinfection technologies only focus on improving disinfection efficiency, without being specifically optimized for the physiological characteristics and aquaculture needs of mandarin fish, and without constructing a complete closed-loop system of "monitoring-decision-disinfection-by-product control-feedback optimization". They cannot simultaneously meet the core needs of efficient disinfection, low irritation, and zero risk of by-products in factory-farmed mandarin fish farming. Summary of the Invention

[0005] The purpose of this invention is to provide a device and method for compound disinfection and disinfection byproduct control in mandarin fish farming. It constructs a multi-factor-linked disinfection decision-making model to replace the traditional "fixed dosage" model, achieving precise matching of "contamination level - pathogen type - disinfection scheme." It integrates three low-irritation disinfection methods, dynamically adjusting the chemical disinfection dosage according to the farming stage. Physical disinfection is the primary method during the seedling stage, while chemical disinfection can be strengthened during the adult stage, balancing efficiency and safety. It achieves integrated "monitoring-removal," specifically removing toxic byproducts such as bromate and residual chlorine, with residual levels far below the tolerance threshold of mandarin fish, preventing secondary pollution. Through optimizations such as low-dose chemical disinfection and aeration / deaeration, it reduces chemical stimulation and bubble stress in the water, adapting to the sensitive characteristics of mandarin fish during the seedling stage.

[0006] To achieve the above objectives, the present invention provides a composite disinfection and disinfection by-product control device for mandarin fish farming, comprising a multi-dimensional monitoring unit, a composite disinfection execution unit, and a by-product monitoring and removal unit connected in sequence, and further comprising a multi-level dynamic disinfection decision unit and a PLC intelligent control unit; The multi-dimensional monitoring unit includes a water quality monitoring module for collecting water quality parameter data of circulating water and a pathogen monitoring module for collecting pathogen concentration data of circulating water. The multi-dimensional monitoring unit transmits the collected data to a multi-level dynamic disinfection decision unit. The multi-level dynamic disinfection decision unit is equipped with a BP neural network model. The BP neural network model is used to receive the data collected by the multi-dimensional monitoring unit and output the appropriate disinfection combination scheme and dosage parameters to the PLC intelligent control unit. The composite disinfection execution unit includes an ultraviolet disinfection module, an ozone generation and dosing module, and an electrolytic water disinfection module. Each module is equipped with a flow regulating valve and a frequency converter. The composite disinfection execution unit is used to receive control instructions from the PLC intelligent control unit and execute the corresponding disinfection operation. The by-product monitoring and removal unit includes a by-product monitoring module and a targeted removal module. The by-product monitoring module is used to collect the concentration data of disinfection by-products in the water after disinfection and transmit it to the PLC intelligent control unit. The targeted removal module is used to receive control commands from the PLC intelligent control unit to target and remove the excessive by-products. The PLC intelligent control unit is connected to the multi-dimensional monitoring unit, the multi-level dynamic disinfection decision unit, the composite disinfection execution unit, and the by-product monitoring and removal unit. The PLC intelligent control unit is used to realize closed-loop linkage control of the entire process.

[0007] Preferably, the water quality monitoring module is located at the inlet of the composite disinfection execution unit. The water quality monitoring module includes a turbidity sensor, a COD sensor, an ammonia nitrogen sensor, a pH sensor, and a water temperature sensor. The accuracy of the turbidity sensor is ±0.1 NTU, the accuracy of the COD sensor is ±5 mg / L, the accuracy of the ammonia nitrogen sensor is ±0.01 mg / L, and the accuracy of the pH sensor is ±0.02. The pathogen monitoring module is located at the water inlet of the composite disinfection execution unit. The pathogen monitoring module is a fluorescence quantitative PCR detector used for targeted monitoring of highly pathogenic microorganisms in mandarin fish, including Aeromonas hydrophila and Flavobacterium columnare. The detection limit of the fluorescence quantitative PCR detector is ≤102 CFU / mL and the detection time is ≤30 min.

[0008] Preferably, the BP neural network model includes an input layer, a hidden layer, and an output layer. The input layer has nodes corresponding to the input parameters of turbidity, COD, ammonia nitrogen, pH, pathogen concentration, and water temperature. The hidden layer has nodes for exploring the nonlinear relationship between water quality parameters, pathogen concentration, and disinfection effect. The output layer has nodes corresponding to the addition coefficients of ultraviolet disinfection, ozone disinfection, and electrolyzed water disinfection, as well as the total disinfection time. The BP neural network model has pre-stored disinfection thresholds for different stages of mandarin fish farming. The model test set decision accuracy is ≥95%, and the decision response time is ≤1 min.

[0009] Preferably, the ultraviolet disinfection module has a wavelength of 254nm and a rated power adjustment range of 50-150W; the ozone generation and dosing module has an ozone output adjustment range of 0.5-3g / h and a dosing concentration adjustment range of 0.1-0.3mg / L; the electrolysis voltage adjustment range of the water electrolysis disinfection module is 5-12V; and the effective chlorine output adjustment range is 5-20mg / h.

[0010] Preferably, the byproduct monitoring module is located at the outlet of the composite disinfection execution unit. The byproduct monitoring module includes a bromate sensor and a residual chlorine sensor. The accuracy of the bromate sensor is ±0.001 mg / L, and the accuracy of the residual chlorine sensor is ±0.01 mg / L. The targeted removal module is located at the outlet of the composite disinfection execution unit. The targeted removal module includes an activated carbon fiber adsorption column, a sodium sulfite reduction column, and a peristaltic pump. The activated carbon fiber adsorption column has an adsorption capacity of ≥80mg / g and an adsorption efficiency of ≥90%. The sodium sulfite reduction column has a packing rate of 30%-40% and a reduction efficiency of ≥95%. The peristaltic pump is used for precise addition of reducing solution.

[0011] Preferably, it also includes a pretreatment unit for pretreating suspended solids in the circulating water of mandarin fish farming. The pretreatment unit is located at the inlet of the multi-dimensional monitoring unit and has an accuracy of 50 μm.

[0012] Preferably, it also includes a mandarin fish physiological stress monitoring unit for collecting stress status data of mandarin fish and transmitting it to a multi-level dynamic disinfection decision unit. The mandarin fish physiological stress monitoring unit is installed inside the aquaculture pond.

[0013] A method for combined disinfection and disinfection byproduct control in mandarin fish farming includes the following steps: S1: The circulating return water is introduced into the pretreatment unit to remove suspended solids in the water, and then sent to the multi-dimensional monitoring unit. The data acquisition cycle is ≤10min. S2: The multi-dimensional monitoring unit collects water quality parameters and pathogen concentration data, and at the same time collects mandarin fish physiological stress status data through the mandarin fish physiological stress monitoring unit. All collected data are synchronously transmitted to the multi-level dynamic disinfection decision unit, which generates disinfection combination schemes and dosage parameters through a BP neural network model. At the same time, the chemical disinfection dosage is adjusted based on the mandarin fish physiological stress status data, and the disinfection combination scheme and the adjusted dosage parameters are transmitted to the PLC intelligent control unit. S3: The PLC intelligent control unit controls the corresponding module of the composite disinfection execution unit to start according to the received disinfection plan, and adjusts the disinfection dosage and operating parameters through the frequency converter. For mandarin fish in the seedling stage, the chemical disinfection dosage is automatically reduced by 30%. S4: After disinfection, the water is introduced into the by-product monitoring and removal unit to monitor the concentration of bromate and residual chlorine in real time. When the by-product concentration exceeds the standard, the PLC intelligent control unit starts the corresponding targeted removal module to reduce the concentration of by-products in the water to below the safe threshold. S5: Every 24 hours, the daily disinfection effect and byproduct concentration data are fed back to the multi-level dynamic disinfection decision unit to iteratively optimize the parameters of the BP neural network model.

[0014] Preferably, in S2, the BP neural network model generates a three-tiered disinfection plan based on the degree of water pollution and pathogen concentration: Low-pollution, low-pathogen operating conditions: turbidity ≤ 5 NTU, pathogen concentration < 10 3 CFU / mL, using a separate UV disinfection protocol, UV power 80-100W, hydraulic retention time 10-15s; Medium-level pollution pathogen conditions: 5 NTU < turbidity ≤ 15 NTU, 10 3 CFU / mL ≤ pathogen concentration < 10 5 CFU / mL, using a combined ultraviolet and low-dose ozone disinfection scheme, with an ozone dosage concentration of 0.1-0.15 mg / L; High pollution and high pathogen conditions: turbidity > 15 NTU, pathogen concentration ≥ 10 5 CFU / mL, using a combined UV and water electrolysis disinfection scheme, with an electrolysis voltage of 8-10V and a UV power of 120-150W.

[0015] Preferably, in S4, the safety thresholds are bromate concentration ≤ 0.01 mg / L and residual chlorine concentration ≤ 0.05 mg / L.

[0016] Therefore, this invention employs the aforementioned composite disinfection and disinfection byproduct control device and method for mandarin fish farming, constructing a multi-factor linkage disinfection decision model to replace the traditional "fixed dosage" mode, achieving precise matching of "contamination level - pathogen type - disinfection scheme"; integrating three low-irritation disinfection methods, dynamically adjusting the chemical disinfection dosage according to the farming stage, with physical disinfection as the main method during the seedling stage and chemical disinfection being strengthened during the adult stage, balancing efficiency and safety; achieving integrated "monitoring-removal", specifically removing toxic byproducts such as bromate and residual chlorine, with residual amounts far below the tolerance threshold of mandarin fish, eliminating secondary pollution; through optimizations such as low-dose chemical disinfection and aeration deaeration, reducing chemical stimulation and bubble stress in the water, adapting to the sensitive characteristics of mandarin fish during the seedling stage.

[0017] The technical solution of the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. Attached Figure Description

[0018] Figure 1 This is a schematic diagram of the structure of the mandarin fish farming compound disinfection and disinfection by-product control device in this invention; Figure 2 This is a flowchart of the method for combined disinfection and disinfection by-product control in mandarin fish farming according to the present invention. Detailed Implementation

[0019] The technical solution of the present invention will be further described below with reference to the accompanying drawings and embodiments.

[0020] Unless otherwise defined, the technical or scientific terms used in this invention shall have the ordinary meaning understood by one of ordinary skill in the art to which this invention pertains. The terms "first," "second," and similar terms used in this invention do not indicate any order, quantity, or importance, but are merely used to distinguish different components. Terms such as "comprising" or "including" mean that the element or object preceding the word encompasses the elements or objects listed following the word and their equivalents, without excluding other elements or objects. Terms such as "connected" or "linked" are not limited to physical or mechanical connections, but can include electrical connections, whether direct or indirect. Terms such as "upper," "lower," "left," and "right" are used only to indicate relative positional relationships; when the absolute position of the described object changes, the relative positional relationship may also change accordingly.

[0021] Example 1 like Figure 1As shown, a composite disinfection and disinfection by-product control device for mandarin fish farming is provided. At the outlet of the aquaculture pond, a multi-dimensional monitoring unit, a composite disinfection execution unit, and a by-product monitoring and removal unit are sequentially connected through pipelines. It also includes a multi-level dynamic disinfection decision unit and a PLC intelligent control unit connected by signals.

[0022] The multi-dimensional monitoring unit is connected to the outlet of the aquaculture pond through pipelines. The multi-dimensional monitoring unit includes a water quality monitoring module and a pathogen monitoring module. The water quality monitoring module is used to collect water quality parameter data of the circulating water, and the pathogen monitoring module is used to collect pathogen concentration data of the circulating water. At the same time, the multi-dimensional monitoring unit transmits the collected water quality parameter data and pathogen concentration data to the multi-level dynamic disinfection decision unit.

[0023] The multi-level dynamic disinfection decision unit has a built-in trained BP neural network model. The BP neural network model is used to receive water quality parameter data and pathogen concentration data collected by the multi-dimensional monitoring unit, process the corresponding data to generate a suitable disinfection combination scheme and dosage parameters, and output the suitable disinfection combination scheme and dosage parameters to the PLC intelligent control unit.

[0024] The composite disinfection execution unit is connected to the outlet of the multi-dimensional monitoring unit through a pipeline. The composite disinfection execution unit is used to receive control commands from the PLC intelligent control unit to execute corresponding disinfection operations. The composite disinfection execution unit integrates three low-irritation disinfection modes, including a series-connected ultraviolet disinfection module, an ozone generation and dosing module, and an electrolyzed water disinfection module. Each module is equipped with a flow regulating valve and a frequency converter, which adjust the disinfection metering and operating parameters of the three disinfection modes.

[0025] The by-product monitoring and removal unit is connected to the outlet of the composite disinfection execution unit through a pipeline. The by-product monitoring and removal unit includes a by-product monitoring module and a targeted removal module. The by-product monitoring module is used to collect the concentration data of disinfection by-products in the disinfected water and transmit it to the PLC intelligent control unit. The targeted removal module is used to receive the control instructions from the PLC intelligent control unit to target and remove the excessive by-products.

[0026] The PLC intelligent control unit is used to realize closed-loop linkage control of the entire process. The PLC intelligent control unit is connected to the multi-dimensional monitoring unit, the multi-level dynamic disinfection decision unit, the composite disinfection execution unit, and the by-product monitoring and removal unit.

[0027] The water quality monitoring module and the pathogen monitoring module are connected sequentially to the inlet of the composite disinfection execution unit via pipelines, and the two are set up in parallel.

[0028] The water quality monitoring module includes a turbidity sensor, a COD sensor, an ammonia nitrogen sensor, a pH sensor, and a water temperature sensor. The accuracy of the turbidity sensor is ±0.1 NTU, the accuracy of the COD sensor is ±5 mg / L, the accuracy of the ammonia nitrogen sensor is ±0.01 mg / L, and the accuracy of the pH sensor is ±0.02.

[0029] The pathogen monitoring module is a real-time PCR instrument, which is used to target and monitor high pathogenic microorganisms in mandarin fish such as Aeromonas hydrophila and Flavobacterium columnare. The detection limit of the real-time PCR instrument is ≤102 CFU / mL and the detection time is ≤30 min.

[0030] The BP neural network model consists of an output layer, two hidden layers, and an input layer. The input layer has six nodes, corresponding to the input parameters of turbidity, COD, ammonia nitrogen, pH, pathogen concentration, and water temperature, respectively. Each hidden layer has thirty-two nodes, which are used to explore the nonlinear relationship between water quality parameters, pathogen concentration, and disinfection effect. The output layer has four nodes, corresponding to the dosage coefficients of ultraviolet disinfection, ozone disinfection, and electrolyzed water disinfection, and the total disinfection time, respectively. The BP neural network model has pre-stored disinfection thresholds for different stages of mandarin fish farming. The model's decision accuracy on the test set is ≥95%, and the decision response time is ≤1 minute.

[0031] The ultraviolet disinfection module uses a 254nm wavelength ultraviolet lamp with a rated power adjustment range of 50-150W. The ozone generation and dosing module has an ozone output adjustment range of 0.5-3g / h and a dosing concentration adjustment range of 0.1-0.3mg / L. The electrolysis voltage of the water electrolysis disinfection module has an adjustment range of 5-12V and an effective chlorine output adjustment range of 5-20mg / h.

[0032] The byproduct monitoring module and the targeted removal module are connected sequentially to the outlet of the composite disinfection unit via pipelines.

[0033] The byproduct monitoring module includes a bromate sensor and a residual chlorine sensor. The accuracy of the bromate sensor is ±0.001 mg / L, and the accuracy of the residual chlorine sensor is ±0.01 mg / L.

[0034] The targeted removal module includes an activated carbon fiber adsorption column and a sodium sulfite reduction column arranged in series. The activated carbon fiber adsorption column has an adsorption capacity of ≥80mg / g and an adsorption efficiency of ≥90%. The sodium sulfite reduction column has a packing rate of 30%-40% and a reduction efficiency of ≥95%. It is equipped with a peristaltic pump to precisely add reducing solution.

[0035] The linkage logic of the targeted removal module is as follows: when the bromate concentration in the water is detected to be >0.01 mg / L, the activated carbon fiber adsorption column is activated; when the residual chlorine concentration in the water is detected to be >0.05 mg / L, the sodium sulfite reduction column is activated, and the amount of reducing solution added is equal to the residual chlorine concentration × the water volume × 1.5.

[0036] A composite disinfection and disinfection by-product control device for mandarin fish farming also includes a pretreatment unit. The pretreatment unit is used to pretreat the circulating water for mandarin fish farming by filtering suspended solids. The pretreatment unit is connected to the inlet of a multi-dimensional monitoring unit through a pipeline, and the accuracy of the pretreatment unit is 50μm.

[0037] A composite disinfection and disinfection by-product control device for mandarin fish farming also includes a mandarin fish physiological stress monitoring unit. The mandarin fish physiological stress monitoring unit is used to collect stress state data of mandarin fish and transmit it to a multi-level dynamic disinfection decision unit. The mandarin fish physiological stress monitoring unit is installed inside the farming pond. Preferably, the mandarin fish physiological stress monitoring unit is deployed underwater by an AI behavior recognition camera module, a water cortisol sensor, and a gill opening and closing frequency monitoring module. It collects the abnormal swimming rate of mandarin fish, gill opening and closing frequency, and water stress hormone cortisol concentration in real time. The data is synchronously transmitted to a BP neural network model. The BP neural network model has built-in stress correction coefficients corresponding to the stress state data.

[0038] like Figure 2 As shown, a method for combined disinfection and disinfection by-product control in mandarin fish farming includes the following steps: S1: The circulating return water is introduced into the pretreatment unit to remove suspended solids in the water, and then sent to the multi-dimensional monitoring unit. The data acquisition cycle is ≤10min.

[0039] S2: The multi-dimensional monitoring unit transmits the collected water quality parameters and pathogen concentration data, and at the same time collects the physiological stress status data of mandarin fish through the mandarin fish physiological stress monitoring unit. All collected data are synchronously transmitted to the multi-level dynamic disinfection decision unit, which generates disinfection combination schemes and dosage parameters through the BP neural network model. At the same time, the chemical disinfection dosage is adjusted based on the physiological stress status data of mandarin fish, and the disinfection combination scheme and the adjusted dosage parameters are transmitted to the PLC intelligent control unit. The BP neural network model generates a three-tiered disinfection plan based on the degree of water pollution and pathogen concentration. Low-pollution, low-pathogen operating conditions: turbidity ≤ 5 NTU, pathogen concentration < 10 3 CFU / mL, using a separate UV disinfection protocol, UV power 80-100W, hydraulic retention time 10-15s; Medium-level pollution pathogen conditions: 5 NTU < turbidity ≤ 15 NTU, 10 3 CFU / mL ≤ pathogen concentration < 10 5CFU / mL, using a combined ultraviolet and low-dose ozone disinfection scheme, with an ozone dosage concentration of 0.1-0.15 mg / L; High pollution and high pathogen conditions: turbidity > 15 NTU, pathogen concentration ≥ 10 5 CFU / mL, using a combined UV and water electrolysis disinfection scheme, with an electrolysis voltage of 8-10V and a UV power of 120-150W.

[0040] S3: The PLC intelligent control unit controls the corresponding module of the composite disinfection execution unit to start according to the received disinfection plan, and adjusts the disinfection dosage and operating parameters through the frequency converter. For mandarin fish in the seedling stage, the chemical disinfection dosage is automatically reduced by 30%.

[0041] S4: After disinfection, the water is introduced into the by-product monitoring and removal unit to monitor the concentration of bromate and residual chlorine in real time. When the by-product concentration exceeds the standard, the PLC intelligent control unit starts the corresponding targeted removal module to reduce the concentration of by-products in the water to below the safe threshold. The safety thresholds are bromate concentration ≤ 0.01 mg / L and residual chlorine concentration ≤ 0.05 mg / L.

[0042] S5: Every 24 hours, the daily disinfection effect and by-product concentration data are fed back to the multi-level dynamic disinfection decision unit to iteratively optimize the parameters of the BP neural network model; The learning rate for parameter iterative optimization is 0.001.

[0043] This embodiment constructs a 100L simulated mandarin fish fry rearing and breeding system, employing the mandarin fish breeding compound disinfection and disinfection by-product control device described in this invention. The specific structure and parameters are as follows: The pretreatment unit uses a 50μm precision microfiltration module; the multi-dimensional monitoring unit's water quality monitoring module includes sensors for turbidity, COD, ammonia nitrogen, pH, and water temperature, while the pathogen monitoring module uses a laboratory-grade fluorescence quantitative PCR detector; the multi-level dynamic disinfection decision unit has a built-in trained BP neural network model with six nodes in the input layer, thirty-two nodes in each of the two hidden layers, and four nodes in the output layer, and pre-stores the disinfection safety threshold during the seedling stage; the composite disinfection execution unit includes a small ultraviolet sterilizer, a micro ozone generator, and a laboratory-grade water electrolysis device, with each module equipped with a frequency converter; the byproduct monitoring and removal unit includes bromate and residual chlorine sensors, as well as a 5L activated carbon fiber adsorption column and a 3L sodium sulfite reduction column; the PLC intelligent control unit realizes closed-loop control of the entire process.

[0044] The experimental subjects in this embodiment were mandarin fish in the fry stage. The initial water quality parameters were: turbidity 8 NTU, COD 25 mg / L, ammonia nitrogen 0.3 mg / L, pH 7.2, and water temperature 25℃. The pathogenic microorganism was Flavobacterium columnare, with an initial concentration of 1.2 × 10⁻⁶. 4The disinfection target is a pathogen removal rate of ≥99% and a byproduct concentration below the safe threshold during the mandarin fish fry stage.

[0045] The operation steps of the control method described in this invention are as follows: S1 Pretreatment: After the aquaculture recirculation water is filtered by the microfiltration module to remove suspended solids, it is sent to the multi-dimensional monitoring unit, and the data acquisition cycle is 5 minutes.

[0046] S2 Dynamic Decision-Making: The multi-dimensional monitoring unit collects water quality parameters and pathogen concentration data, and simultaneously collects physiological stress status data of mandarin fish through the mandarin fish physiological stress monitoring unit. All collected data are synchronously transmitted to the BP neural network model. The model determines that the condition is moderate pollution and moderate pathogens, and outputs a composite disinfection scheme of ultraviolet and low-dose ozone. The specific parameters are: ultraviolet power 80W, ozone dosage concentration 0.1mg / L, and hydraulic residence time 12s, which are transmitted to the PLC intelligent control unit.

[0047] S3 Composite Disinfection Execution: The PLC intelligent control unit activates the ultraviolet disinfection module and the ozone generation and dosing module according to the plan. Due to the seedling stage, the ozone dosage is automatically reduced by 30%, and the actual dosage concentration is 0.07mg / L.

[0048] S4 Byproduct Monitoring and Removal: After disinfection, the water was tested by the byproduct monitoring module. The bromate concentration was 0.006 mg / L and the residual chlorine concentration was 0.04 mg / L, both of which were below the safety threshold. There was no need to activate the targeted removal subunit, and the qualified water was returned to the aquaculture pond.

[0049] S5 Feedback Optimization: After running continuously for 24 hours, the disinfection effect and by-product data are fed back to the decision model to complete one parameter iteration optimization.

[0050] The results of this embodiment are as follows: after disinfection, the concentration of Flavobacterium columnare in the water decreased to 8 CFU / mL, with a removal rate of 99.93%; the concentration of by-products was far below the safety threshold for mandarin fish during the seedling stage; after 7 days of continuous operation, the mandarin fish during the seedling stage showed no stress response and the survival rate reached 94%, which verified the excellent disinfection effect and adaptability of the present invention to the seedling stage.

[0051] Example 2 The application scenario of this embodiment is an 800m aquaculture base. 3 The mandarin fish fry rearing pond is used to raise mandarin fish fry with a body length of 2-3 cm at a stocking density of 80 fish / m². 3 It is equipped with a "one main and multiple auxiliary" factory-style circulating water system, and the circulating water is disinfected using the device and method described in this invention.

[0052] The specific configuration of the device in this embodiment includes: a multi-dimensional monitoring unit equipped with six sets of water quality sensors and two online quantitative PCR detectors; and a composite disinfection execution unit designed to process a flow rate of 160 m³ / h. 3 The UV disinfection module has an adjustable rated power of 50-150W, the ozone generation and dosing module has an adjustable output of 0.5-3g / h, and the electrolysis voltage of the water electrolysis disinfection module is adjustable from 5-12V. The by-product monitoring and removal unit is equipped with two sets of parallel activated carbon fiber adsorption columns and sodium sulfite reduction columns. The PLC intelligent control unit is seamlessly integrated with the existing circulating water system and disease early warning system.

[0053] This embodiment operated continuously for 90 days, employing the control method described in this invention. The system dynamically adjusted the disinfection plan based on real-time monitoring of water quality fluctuations and pathogen concentrations: 60% of the time, low-pollution, low-pathogen conditions were handled with UV disinfection alone; 40% of the time, medium-to-high-pollution conditions were handled with a combined UV and low-dose ozone disinfection plan. During operation, three pathogen concentration increases were detected, with the highest pathogen concentration reaching 2.5 × 10⁻⁶. 5 With a concentration of CFU / mL, the system automatically switches to a combined UV and electrolyzed water disinfection scheme, reducing the pathogen concentration to a safe range within 24 hours, with no disease outbreaks.

[0054] The operational results of this embodiment are as follows: After 90 days of continuous operation, the survival rate of mandarin fish during the seedling stage reached 93.5%, which is 23.5% higher than the traditional ozone disinfection mode at this base; the concentration of water by-products was stably controlled at bromate 0.005-0.009 mg / L and residual chlorine 0.02-0.04 mg / L, which fully met the safety requirements during the seedling stage, and there were no cases of chemical irritation-related mortality; the amount of chemical disinfectant used was reduced by 42% compared with the traditional mode, and the disinfection cost was reduced by 36%, which verifies the excellent application effect and economic benefits of this invention in the factory-scale mandarin fish farming scenario.

[0055] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit them. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can still be made to the technical solutions of the present invention, and these modifications or equivalent substitutions cannot cause the modified technical solutions to deviate from the spirit and scope of the technical solutions of the present invention.

Claims

1. A composite disinfection and disinfection by-product control device for mandarin fish farming, characterized in that: It includes a multi-dimensional monitoring unit, a composite disinfection execution unit, and a byproduct monitoring and removal unit connected in sequence, as well as a multi-level dynamic disinfection decision unit and a PLC intelligent control unit; The multi-dimensional monitoring unit includes a water quality monitoring module for collecting water quality parameter data of circulating water and a pathogen monitoring module for collecting pathogen concentration data of circulating water. The multi-dimensional monitoring unit transmits the collected data to the multi-level dynamic disinfection decision unit. The multi-level dynamic disinfection decision unit is equipped with a BP neural network model. The BP neural network model is used to receive the data collected by the multi-dimensional monitoring unit and output the appropriate disinfection combination scheme and dosage parameters to the PLC intelligent control unit. The composite disinfection execution unit includes an ultraviolet disinfection module, an ozone generation and dosing module, and an electrolytic water disinfection module. Each module is equipped with a flow regulating valve and a frequency converter. The composite disinfection execution unit is used to receive control commands from the PLC intelligent control unit and execute corresponding disinfection operations. The byproduct monitoring and removal unit includes a byproduct monitoring module and a targeted removal module. The byproduct monitoring module is used to collect the concentration data of disinfection byproducts in the water after disinfection and transmit it to the PLC intelligent control unit. The targeted removal module is used to receive the control instructions from the PLC intelligent control unit to target and remove the excessive byproducts. The PLC intelligent control unit is connected to the multi-dimensional monitoring unit, the multi-level dynamic disinfection decision unit, the composite disinfection execution unit, and the by-product monitoring and removal unit, respectively. The PLC intelligent control unit is used to realize closed-loop linkage control of the entire process.

2. The mandarin fish farming compound disinfection and disinfection by-product control device according to claim 1, characterized in that: The water quality monitoring module is located at the inlet of the composite disinfection execution unit. The water quality monitoring module includes a turbidity sensor, a COD sensor, an ammonia nitrogen sensor, a pH sensor, and a water temperature sensor. The accuracy of the turbidity sensor is ±0.1 NTU, the accuracy of the COD sensor is ±5 mg / L, the accuracy of the ammonia nitrogen sensor is ±0.01 mg / L, and the accuracy of the pH sensor is ±0.

02. The pathogen monitoring module is located at the water inlet of the composite disinfection execution unit. The pathogen monitoring module is a real-time fluorescence PCR detector used for targeted monitoring of highly pathogenic microorganisms in mandarin fish, including Aeromonas hydrophila and Flavobacterium columnare. The detection limit of the real-time fluorescence PCR detector is ≤10. 2 CFU / mL, detection time ≤30min.

3. The mandarin fish farming compound disinfection and disinfection by-product control device according to claim 1, characterized in that: The BP neural network model includes an input layer, a hidden layer, and an output layer. The input layer has nodes corresponding to turbidity, COD, ammonia nitrogen, pH, pathogen concentration, and water temperature. The hidden layer has nodes for exploring the nonlinear relationship between water quality parameters, pathogen concentration, and disinfection effect. The output layer has nodes corresponding to the dosage coefficients and total disinfection time for ultraviolet disinfection, ozone disinfection, and electrolyzed water disinfection. The BP neural network model pre-stores disinfection thresholds for different stages of mandarin fish farming. The model's decision accuracy on the test set is ≥95%, and the decision response time is ≤1 minute.

4. The mandarin fish farming compound disinfection and disinfection by-product control device according to claim 1, characterized in that: The ultraviolet disinfection module has a wavelength of 254nm and a rated power adjustment range of 50-150W. The ozone generation and dosing module has an ozone output adjustment range of 0.5-3g / h and a dosing concentration adjustment range of 0.1-0.3mg / L. The electrolysis voltage adjustment range of the water electrolysis disinfection module is 5-12V, and the effective chlorine output adjustment range is 5-20mg / h.

5. The mandarin fish farming compound disinfection and disinfection by-product control device according to claim 1, characterized in that: The byproduct monitoring module is located at the outlet of the composite disinfection execution unit. The byproduct monitoring module includes a bromate sensor and a residual chlorine sensor. The accuracy of the bromate sensor is ±0.001 mg / L, and the accuracy of the residual chlorine sensor is ±0.01 mg / L. The targeted removal module is located at the outlet of the composite disinfection execution unit. The targeted removal module includes an activated carbon fiber adsorption column, a sodium sulfite reduction column, and a peristaltic pump. The activated carbon fiber adsorption column has an adsorption capacity ≥80mg / g and an adsorption efficiency ≥90%. The sodium sulfite reduction column has a packing rate of 30%-40% and a reduction efficiency ≥95%. The peristaltic pump is used for precise addition of reducing solution.

6. The mandarin fish farming compound disinfection and disinfection by-product control device according to claim 1, characterized in that: It also includes a pretreatment unit for filtering suspended solids in the circulating water of mandarin fish farming. The pretreatment unit is located at the inlet of the multi-dimensional monitoring unit and has an accuracy of 50 μm.

7. The mandarin fish farming compound disinfection and disinfection by-product control device according to claim 1, characterized in that: It also includes a mandarin fish physiological stress monitoring unit for collecting stress status data of mandarin fish and transmitting it to the multi-level dynamic disinfection decision unit, wherein the mandarin fish physiological stress monitoring unit is installed inside the aquaculture pond.

8. A method for combined disinfection and disinfection byproduct control in mandarin fish farming, based on the apparatus described in any one of claims 1-7, characterized in that, Includes the following steps: S1: The circulating return water is introduced into the pretreatment unit to remove suspended solids in the water, and then sent to the multi-dimensional monitoring unit. The data acquisition cycle is ≤10min. S2: The multi-dimensional monitoring unit collects water quality parameters and pathogen concentration data, and at the same time collects mandarin fish physiological stress status data through the mandarin fish physiological stress monitoring unit. All collected data are synchronously transmitted to the multi-level dynamic disinfection decision unit, which generates disinfection combination schemes and dosage parameters through a BP neural network model. At the same time, the chemical disinfection dosage is adjusted based on the mandarin fish physiological stress status data, and the disinfection combination scheme and the adjusted dosage parameters are transmitted to the PLC intelligent control unit. S3: The PLC intelligent control unit controls the corresponding module of the composite disinfection execution unit to start according to the received disinfection plan, and adjusts the disinfection dosage and operating parameters through the frequency converter. For mandarin fish in the seedling stage, the chemical disinfection dosage is automatically reduced by 30%. S4: After disinfection, the water is introduced into the by-product monitoring and removal unit to monitor the concentration of bromate and residual chlorine in real time. When the by-product concentration exceeds the standard, the PLC intelligent control unit starts the corresponding targeted removal module to reduce the concentration of by-products in the water to below the safe threshold. S5: Every 24 hours, the daily disinfection effect and byproduct concentration data are fed back to the multi-level dynamic disinfection decision unit to iteratively optimize the parameters of the BP neural network model.

9. The method for compound disinfection and disinfection by-product control in mandarin fish farming according to claim 8, characterized in that: In S2, the BP neural network model generates a three-tiered disinfection plan based on the degree of water pollution and pathogen concentration: Low-pollution, low-pathogen operating conditions: turbidity ≤ 5 NTU, pathogen concentration < 10 3 CFU / mL, using a separate UV disinfection protocol, UV power 80-100W, hydraulic retention time 10-15s; Medium-level pollution pathogen conditions: 5 NTU < turbidity ≤ 15 NTU, 10 3 CFU / mL ≤ pathogen concentration < 10 5 CFU / mL, using a combined ultraviolet and low-dose ozone disinfection scheme, with an ozone dosage concentration of 0.1-0.15 mg / L; High pollution and high pathogen conditions: turbidity > 15 NTU, pathogen concentration ≥ 10 5 CFU / mL, using a combined UV and water electrolysis disinfection scheme, with an electrolysis voltage of 8-10V and a UV power of 120-150W.

10. The method for compound disinfection and disinfection by-product control in mandarin fish farming according to claim 8, characterized in that: In step S4, the safety thresholds are bromate concentration ≤ 0.01 mg / L and residual chlorine concentration ≤ 0.05 mg / L.

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