Intelligent tail water treatment system for aquaculture

Abstract

The application provides a tail water intelligent processing system for aquaculture, which adjusts the extraction operation state of tail water extracted from the culture pond according to the pond water circulation state of the culture pond, so as to extract the tail water to the filter pond; the filter equipment of the filter pond is visually monitored to obtain the filter state information of the filter equipment, so as to adjust the filter operation state of the filter equipment, and the tail water after filtration is transferred to the sedimentation pond, so as to improve the filtering effectiveness and completeness of the tail water; the sedimentation pond is also visually monitored to determine the water body feature information corresponding to the water body part capable of being transferred to the disinfection pond inside the sedimentation pond, so as to adjust the transfer operation state of the water body part transferred to the disinfection pond, and avoid the transfer of the sediment to the disinfection pond; the tail water in the disinfection pond is further sampled and analyzed to obtain the colony distribution feature information of the tail water, so as to adjust the conveying operation state of the disinfection gas conveyed to the disinfection pond, so as to ensure the global disinfection efficiency of the water body and shorten the disinfection time.

Description

Technical Field

[0001] This invention relates to the field of water treatment, and more particularly to an intelligent wastewater treatment system for aquaculture. Background Technology

[0002] Aquaculture requires maintaining good water quality. During the aquaculture process, feed and aquatic excrement both affect water quality. To provide a clean water environment, water circulation is necessary, involving the introduction of clean water into the aquaculture ponds and the discharge of water from the ponds. The water discharged from the ponds is typically called wastewater. Wastewater is characterized by high nutrient content and low oxygen levels; directly discharging it into the environment will cause pollution. Therefore, wastewater needs appropriate purification treatment before discharge. Existing wastewater treatment methods typically include sedimentation and bacterial disinfection, but these methods do not provide sufficient and effective purification and cannot efficiently improve the water quality of the wastewater. Summary of the Invention

[0003] The purpose of this invention is to provide an intelligent wastewater treatment system for aquaculture. Based on the water circulation status of the aquaculture pond, the system adjusts the wastewater extraction operation to draw the wastewater into a filtration pond. Visual monitoring of the filtration equipment in the filtration pond reveals its filtration status, allowing for adjustments to the filtration operation. The filtered wastewater is then transferred to a sedimentation pond, improving the effectiveness and thoroughness of filtration. Furthermore, visual monitoring of the sedimentation pond identifies water characteristics that can be transferred to a disinfection pond, adjusting the transfer operation to prevent sediment from being transferred. Finally, the wastewater in the disinfection pond is sampled and analyzed to obtain bacterial distribution characteristics, adjusting the delivery of disinfectant gas to ensure overall disinfection efficiency while reducing disinfection time, effectively improving wastewater quality.

[0004] This invention is achieved through the following technical solution:

[0005] A smart wastewater treatment system for aquaculture includes:

[0006] The tailwater extraction module is used to adjust the extraction operation state of the tailwater extraction from the aquaculture pond according to the water circulation state of the aquaculture pond, so as to extract the tailwater to the filtration pond.

[0007] A filter visual recognition module is used to visually monitor the filtration equipment in the filter pool, obtain corresponding dynamic images of the filtration, and analyze the dynamic images of the filtration to determine the filtration status information of the filtration equipment.

[0008] The filtration control module is used to adjust the filtration operation status of the filtration equipment according to the filtration status information, so as to transfer the filtered effluent to the sedimentation tank.

[0009] A sedimentation visual recognition module is used to visually monitor the sedimentation tank, obtain dynamic images of sedimentation inside the sedimentation tank, and analyze the dynamic images of sedimentation to determine the water feature information corresponding to the portion of water inside the sedimentation tank that can be transferred to the disinfection tank.

[0010] The water transfer control module is used to adjust the transfer operation status of the water body portion to the disinfection pool based on the water body characteristic information.

[0011] The colony analysis module is used to sample and analyze the effluent in the disinfection tank to obtain the colony distribution characteristics of the effluent.

[0012] The colony elimination control module is used to adjust the delivery operation status of the disinfection gas to the disinfection pool based on the colony distribution characteristic information.

[0013] Optionally, the wastewater extraction module is used to adjust the extraction operation state of wastewater extraction from the aquaculture pond according to the water circulation state of the aquaculture pond, thereby extracting the wastewater to the filtration pond, including:

[0014] The flow rates of the input and output water in the aquaculture pond are obtained. Based on the flow rate difference between the input and output water flow rates, the maximum flow rate of wastewater that can be extracted from the aquaculture pond when the water depth inside the aquaculture pond is maintained within a preset depth range is estimated. Based on the maximum flow rate, the extraction flow rate of wastewater from the aquaculture pond is adjusted so that the wastewater is extracted to the filtration pond.

[0015] Optionally, the filter visual recognition module is used to perform visual monitoring of the filtration equipment in the filter pool to obtain corresponding dynamic filtration images; and to analyze the dynamic filtration images to determine the filtration status information of the filtration equipment, including:

[0016] The filtration equipment in the filtration tank is dynamically photographed to obtain dynamic images of the filtration operation of the filtration equipment on the effluent; the dynamic images of the filtration operation are then processed into frames to obtain several filtration operation image frames.

[0017] The image frame of the filtration operation is processed to obtain the average particle size of impurities in the effluent after filtration by the filtration device; the average particle size of impurities is compared with a preset particle size threshold. If the average particle size of impurities is greater than or equal to the preset particle size threshold, it is determined that the filtration device has not effectively filtered the effluent; otherwise, it is determined that the filtration device has effectively filtered the effluent.

[0018] Optionally, the filtration control module is used to adjust the filtration operation state of the filtration equipment according to the filtration status information, thereby transferring the filtered effluent to a sedimentation tank, including:

[0019] When the filtration device effectively filters the effluent, the filtration pump flow rate of the effluent is kept constant, thereby transferring the filtered effluent to the sedimentation tank.

[0020] If the filtration device fails to effectively filter the effluent, the pumping flow rate of the filtration device for the effluent is reduced, thereby transferring the filtered effluent to a sedimentation tank.

[0021] Optionally, the sedimentation visual recognition module is used to visually monitor the sedimentation tank to obtain dynamic images of sedimentation inside the sedimentation tank; and to analyze the dynamic images of sedimentation to determine the water feature information corresponding to the portion of water inside the sedimentation tank that can be transferred to the disinfection tank, including:

[0022] The sedimentation tank is photographed with binoculars to obtain a dynamic binocular image of sedimentation inside the sedimentation tank; based on the binocular parallax of the dynamic binocular image of sedimentation, a corresponding dynamic three-dimensional image of sedimentation is generated.

[0023] The dynamic three-dimensional image of the sedimentation is analyzed to obtain the top boundary contour feature information of the sediment inside the sedimentation tank; based on the top boundary contour feature information of the sediment, it is determined whether the sedimentation tank is in a stable sedimentation state.

[0024] When the water in the sedimentation tank is in a stable sedimentation state, the water distribution range information corresponding to the portion of the water inside the sedimentation tank that can be transferred to the disinfection tank is determined based on the top boundary contour feature information of the sediment.

[0025] Optionally, the water transfer control module is used to adjust the transfer operation status of the water body portion transferred to the disinfection tank according to the water body characteristic information, including:

[0026] Based on the water body distribution range information, the water body extraction range transferred to the disinfection tank is determined; and based on the change state of the top boundary contour feature information of the sediment during the extraction process of the water body, the extraction flow rate of the water body is adjusted.

[0027] Optionally, the colony analysis module is used to sample and analyze the effluent in the disinfection tank to obtain colony distribution characteristic information of the effluent, including:

[0028] Distributed sampling analysis was performed on the effluent at different locations inside the disinfection tank to obtain the colony concentration information corresponding to each location. The colony concentration information corresponding to the effluent at all locations was integrated and simulated to obtain the global colony concentration distribution information of the water body inside the disinfection tank.

[0029] Optionally, the colony analysis module performs distributed sampling analysis on the effluent at different locations inside the disinfection tank to obtain the colony concentration information corresponding to each location of the effluent, including:

[0030] Step S1: Under aseptic conditions, take a certain amount of the sample to be tested and dissolve it in sterile water. Shake thoroughly until well mixed to prepare a sample solution. Dilute the sample solution using a 10-fold series of concentration gradient standards and dispense it into different test tubes. Inject or spread a quantitative amount of the dilution onto agar plates and incubate under the fixed temperature and time conditions specified in the standard to obtain colony plates. Count the number of colonies using electronic auxiliary equipment. Let N be... ci Let C be the colony count result of the i-th colony plate at a dilution factor of C. Then, the mean colony count of the sampled specimen at a dilution factor of C is:

[0031]

[0032] In the above formula (1), is the mean colony count of the sample at a dilution factor of C; m is the number of colony plates at a dilution factor of C; i is the colony plate number, which is an integer greater than or equal to 1 and less than or equal to m;

[0033] Step S2: Based on the calculation results of step S1 above, calculate the number of colonies obtained by dilution factor C of the sample. The calculation formula is as follows:

[0034]

[0035] In the above formula (2), N c This represents the number of colonies obtained from the sample after dilution by a concentration factor of C, where C is the dilution factor.

[0036] Step S3: Based on the calculation results of step S2 above, calculate the actual number of colonies in the sampled sample. The determination process is as follows:

[0037] If only one dilution plate has a colony count within the preset range, i.e., only one N... c If the value of N is between 30 and 300, then N c The value represents the total number of bacterial colonies in the sample.

[0038] If two consecutive dilutions have colony counts within the preset counting range, that is, if there are two N... c The value is between 30 and 300, denoted as N. c1 and N c2 The actual number of colonies in the sample is:

[0039]

[0040] in and These are the mean colony counts at dilution concentrations C1 and C2, respectively, with dilution concentration C1 being less than dilution concentration C2.

[0041] If the colony count on all dilutions is greater than 300, that is, all N... c If all values ​​are greater than 300, then the number of colonies on the plate with the highest dilution concentration is taken as the true number of colonies in the sample.

[0042] If the colony count on all dilutions is less than 30, that is, all N... c If all values ​​are less than 30, then the number of colonies on the plate with the highest dilution and lowest concentration is taken as the true number of colonies in the sample.

[0043] Then, based on the actual number of colonies, the colony concentration information corresponding to each location of the effluent is obtained.

[0044] Optionally, the colony analysis module performs distributed sampling analysis on the effluent at different locations inside the disinfection tank to obtain the colony concentration information corresponding to each location of the effluent, including:

[0045] Step A1: Take pictures of the tailwater at each location to obtain corresponding tailwater images; perform visual recognition on the tailwater images to obtain the particle distribution information of the bacterial colonies in the tailwater; use the following formula (1) to obtain the average particle size of the particles formed by the bacterial colonies at the corresponding locations in the tailwater in the image dimension based on the edge position points of each bacterial colony.

[0046]

[0047] In the above formula (1), This represents the average particle size of the particles formed by the a-th colony in the tailwater at the k-th location along the image dimension; [X] k_a (p),Y k_a [p] represents the coordinates of the p-th edge point of the particle formed by the a-th colony in the tailwater at position k; B represents the set of edge point points of the a-th colony in the tailwater at position k; max p∈B [X k_a[p] represents the maximum x-coordinate of the edge position of the particle formed by the a-th colony in the tailwater at position k; max p∈B [Y k_a [p] represents the maximum ordinate value of the edge position point of the particle formed by the a-th colony in the tailwater at the k-th position; min p∈B [X k_a [p] represents the minimum x-coordinate of the edge position point of the particle formed by the a-th colony in the tailwater at position k; min p∈B [Y k_a [p] represents the minimum ordinate value of the edge position point of the particle formed by the a-th colony in the tailwater at the k-th position;

[0048] Step A2: Using formula (2) below, based on the position of the marked point in the tailwater image at each location and the average particle size of each colony formed in the tailwater along the image dimension, obtain the actual particle size of each colony in the tailwater at each location.

[0049]

[0050] In the above formula (2), D(k_a) represents the actual particle size of the a-th colony in the tailwater at the k-th position; (x1,y1) represents the coordinate value of the first marker point in the tailwater image at the k-th position; (x2,y2) represents the coordinate value of the second marker point in the tailwater image at the k-th position; and L represents the actual distance between the first marker point and the second marker point.

[0051] Step A3: Using the formula (3) below, based on the actual particle size of each colony in the effluent at each location and the average number of colonies per unit area, obtain the number of colonies in the effluent at each location.

[0052]

[0053] In the above formula (3), E(k) represents the number of colonies in the tailwater at the k-th position; S0 represents the unit area; E0 represents the average number of colonies per unit area; and A represents the total number of colonies in the tailwater at the k-th position.

[0054] Optionally, the colony elimination control module is used to adjust the delivery operation state of the disinfection gas to the disinfection tank according to the colony distribution characteristic information, including:

[0055] Based on the colony concentration distribution information, the entire water body inside the disinfection pool is divided into several low-colony-concentration water body sub-regions and several high-colony-concentration water body sub-regions; based on the average colony concentration values ​​of the low-colony-concentration water body sub-regions and the high-colony-concentration water body sub-regions, the ozone delivery flow rate and delivery duration to the low-colony-concentration water body sub-regions and the high-colony-concentration water body sub-regions are adjusted.

[0056] Compared with the prior art, the present invention has the following beneficial effects:

[0057] The intelligent wastewater treatment system for aquaculture provided in this application adjusts the wastewater extraction operation based on the water circulation status of the aquaculture pond, thereby drawing the wastewater to a filtration pond. Visual monitoring of the filtration equipment in the filtration pond yields filtration status information, which is then used to adjust the filtration operation. The filtered wastewater is then transferred to a sedimentation pond, improving the effectiveness and thoroughness of filtration. Visual monitoring of the sedimentation pond further identifies water characteristics that can be transferred to a disinfection pond, adjusting the transfer operation to prevent sediment from being transferred. Finally, the wastewater in the disinfection pond is sampled and analyzed to obtain bacterial distribution characteristics, adjusting the delivery of disinfectant gas to ensure overall disinfection efficiency while shortening disinfection time, effectively improving the wastewater quality. Attached Figure Description

[0058] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort. Wherein:

[0059] Figure 1 This is a schematic diagram of the structure of an intelligent wastewater treatment system for aquaculture provided by the present invention. Detailed Implementation

[0060] To make the above-mentioned objectives, features, and advantages of this application more apparent and understandable, the specific embodiments of this application will be described in detail below with reference to the accompanying drawings. It should be understood that the specific embodiments described herein are for illustrative purposes only and are not intended to limit the scope of this application. Furthermore, it should be noted that, for ease of description, only the parts relevant to this application are shown in the accompanying drawings, not the entire structure. Based on the embodiments in this application, all other embodiments obtained by those skilled in the art without inventive effort are within the scope of protection of this application.

[0061] The terms “comprising” and “having”, and any variations thereof, used in this application are intended to cover non-exclusive inclusion. For example, a process, method, system, product, or apparatus that includes a series of steps or units is not limited to the steps or units listed, but may optionally include steps or units not listed, or may optionally include other steps or units inherent to such process, method, product, or apparatus.

[0062] In this document, the term "embodiment" means that a particular feature, structure, or characteristic described in connection with an embodiment may be included in at least one embodiment of this application. The appearance of this phrase in various places throughout the specification does not necessarily refer to the same embodiment, nor is it a separate or alternative embodiment mutually exclusive with other embodiments. It will be explicitly and implicitly understood by those skilled in the art that the embodiments described herein can be combined with other embodiments.

[0063] Please see Figure 1 As shown in the figure, an embodiment of this application provides an intelligent wastewater treatment system for aquaculture. This intelligent wastewater treatment system for aquaculture includes:

[0064] The tailwater extraction module is used to adjust the extraction operation state of the tailwater extraction from the aquaculture pond according to the water circulation state of the aquaculture pond, so as to extract the tailwater to the filtration pond.

[0065] The filter visual recognition module is used to visually monitor the filtration equipment of the filter pool, obtain corresponding dynamic images of the filtration, and analyze the dynamic images of the filtration to determine the filtration status information of the filtration equipment.

[0066] The filtration control module is used to adjust the filtration operation status of the filtration equipment according to the filtration status information, so as to transfer the filtered effluent to the sedimentation tank.

[0067] The sedimentation visual recognition module is used to visually monitor the sedimentation tank and obtain dynamic images of sedimentation inside the sedimentation tank; and to analyze the dynamic images of sedimentation to determine the water feature information corresponding to the water part inside the sedimentation tank that can be transferred to the disinfection tank.

[0068] The water transfer control module is used to adjust the transfer operation status of the water body to the disinfection pool based on the water body's characteristic information.

[0069] The colony analysis module is used to sample and analyze the effluent in the disinfection tank to obtain information on the colony distribution characteristics of the effluent.

[0070] The colony elimination control module is used to adjust the delivery operation status of the disinfection gas to the disinfection pool based on the colony distribution characteristics.

[0071] The beneficial effects of the above embodiments are as follows: the intelligent wastewater treatment system for aquaculture adjusts the wastewater extraction operation based on the water circulation status of the aquaculture pond, thereby extracting the wastewater to the filtration pond; visually monitors the filtration equipment in the filtration pond to obtain filtration status information, and adjusts the filtration operation accordingly, transferring the filtered wastewater to the sedimentation pond to improve the filtration effectiveness and thoroughness; visually monitors the sedimentation pond to determine the water characteristics of the portion of the water that can be transferred to the disinfection pond, and adjusts the transfer operation accordingly to prevent sediment from being transferred to the disinfection pond; and samples and analyzes the wastewater in the disinfection pond to obtain bacterial colony distribution characteristics, and adjusts the delivery operation of the disinfection gas to the disinfection pond, ensuring overall disinfection efficiency while shortening disinfection time and effectively improving the wastewater quality.

[0072] In another embodiment, the wastewater extraction module is used to adjust the extraction operation state of extracting wastewater from the aquaculture pond according to the water circulation state of the aquaculture pond, thereby extracting the wastewater to the filtration pond, including:

[0073] The flow rates of the input and output water in the aquaculture pond are obtained. Based on the flow rate difference between the input and output water flow rates, the maximum flow rate of wastewater that can be extracted from the aquaculture pond when the water depth inside the aquaculture pond is maintained within a preset depth range is estimated. Based on the maximum flow rate, the extraction flow rate of wastewater from the aquaculture pond is adjusted so that the wastewater is extracted to the filtration pond.

[0074] The beneficial effects of the above embodiments are as follows: In order to ensure that the water body inside the aquaculture pond can maintain a relatively stable dynamic equilibrium state during the process of extracting tailwater from the aquaculture pond, the inflow rate of the input pond and the outflow rate of the output pond are obtained. Based on the flow rate difference between the inflow rate of the input pond and the outflow pond, the maximum flow rate value of tailwater that can be extracted from the aquaculture pond when the water depth inside the aquaculture pond is maintained within a preset depth range is estimated. Then, based on the maximum flow rate value, the extraction flow rate of tailwater from the aquaculture pond is determined so that the extraction flow rate does not exceed the maximum flow rate value, thereby avoiding the impact on the water volume in the aquaculture pond due to excessive extraction of tailwater.

[0075] In another embodiment, the filter visual recognition module is used to visually monitor the filtration equipment of the filter pool to obtain corresponding dynamic filtration images; and to analyze the dynamic filtration images to determine the filtration status information of the filtration equipment, including:

[0076] The filtration equipment in the filtration tank was dynamically photographed to obtain dynamic images of the filtration operation of the filtration equipment on the effluent; the dynamic images of the filtration operation were then processed into frames to obtain several filtration operation image frames.

[0077] The image frame of the filtration operation is processed to obtain the average particle size of impurities in the effluent after filtration by the filtration device. The average particle size of the impurities is compared with a preset particle size threshold. If the average particle size of the impurities is greater than or equal to the preset particle size threshold, it is determined that the filtration device has not effectively filtered the effluent; otherwise, it is determined that the filtration device has effectively filtered the effluent.

[0078] The beneficial effects of the above embodiments are that by dynamically capturing images of the filtration equipment in the filtration tank, dynamic images of the filtration operation of the filtration equipment on the effluent can be obtained. This allows for visual identification and analysis of the effluent after filtration, obtaining the average particle size of impurities inside the effluent after filtration, thereby quantitatively identifying the water quality status of the filtered effluent. The average particle size of the impurities is then compared with a preset particle size threshold. If the average particle size of the impurities is greater than or equal to the preset particle size threshold, it is determined that the filtration equipment has not effectively filtered the effluent; otherwise, it is determined that the filtration equipment has effectively filtered the effluent. This provides a reliable basis for subsequent adjustments to the operating status of the filtration equipment.

[0079] In another embodiment, the filtration control module is used to adjust the filtration operation state of the filtration device according to the filtration status information, thereby transferring the filtered effluent to a sedimentation tank, including:

[0080] When the filtration equipment effectively filters the effluent, the filtration pump flow rate of the effluent remains unchanged, thereby transferring the filtered effluent to the sedimentation tank.

[0081] If the filtration equipment fails to effectively filter the effluent, the pumping flow rate of the filtration equipment for the effluent is reduced, thereby transferring the filtered effluent to the sedimentation tank.

[0082] The beneficial effects of the above embodiments are that when the filtration device effectively filters the effluent, the pump flow rate of the filtration device for the effluent remains constant, thereby transferring the filtered effluent to the sedimentation tank, which ensures the normal and stable operation of the filtration device. When the filtration device does not effectively filter the effluent, the pump flow rate of the filtration device for the effluent is reduced, thereby transferring the filtered effluent to the sedimentation tank. This increases the retention time of the effluent in the filtration device, improving the filtration efficiency and thoroughness of the filtration device.

[0083] In another embodiment, the sedimentation visual recognition module is used to visually monitor the sedimentation tank, obtain dynamic images of sedimentation inside the sedimentation tank, and analyze the dynamic images of sedimentation to determine the water feature information corresponding to the portion of water inside the sedimentation tank that can be transferred to the disinfection tank, including:

[0084] The sedimentation tank is photographed with binoculars to obtain a dynamic binocular image of the sedimentation inside the tank; based on the binocular parallax of the dynamic binocular image of the sedimentation, a corresponding dynamic three-dimensional image of the sedimentation is generated.

[0085] The dynamic three-dimensional image of the sedimentation was analyzed to obtain the top boundary contour feature information of the sediment inside the sedimentation tank. Based on the top boundary contour feature information of the sediment, it was determined whether the water in the sedimentation tank was in a stable sedimentation state.

[0086] When the water in the sedimentation tank is in a stable sedimentation state, the water distribution range corresponding to the portion of the water inside the sedimentation tank that can be transferred to the disinfection tank is determined based on the contour feature information of the top boundary of the sediment.

[0087] The beneficial effects of the above embodiments are that by performing binocular imaging on the sedimentation tank, dynamic binocular images of the sedimentation process inside the tank are obtained, and corresponding dynamic three-dimensional images of the sedimentation process are generated. From these dynamic three-dimensional images, the top boundary contour features of the sediment within the sedimentation tank (i.e., the top boundary contour features of the sediment already settled at the bottom of the sedimentation tank) can be identified. This allows for the identification of the sediment accumulation amount and stability of the sediment in the sedimentation tank. Based on these top boundary contour features, it is determined whether the top boundary contour is stable within a preset time interval, thereby determining whether the sedimentation tank water is in a stable sedimentation state. This ensures that water can be extracted after complete sedimentation, preventing sediment from being extracted into the disinfection tank. Furthermore, when the sedimentation tank water is in a stable sedimentation state, the distribution range of water within the sedimentation tank that can be transferred to the disinfection tank is determined based on the top boundary contour features, ensuring the accuracy of water extraction.

[0088] In another embodiment, the water transfer control module is used to adjust the transfer operation status of the water body portion to the disinfection tank based on the water body characteristic information, including:

[0089] Based on the water body distribution information, the extraction range of the water body transferred to the disinfection pool is determined; and based on the change in the top boundary outline of the sediment during the extraction process, the extraction flow rate of the water body is adjusted.

[0090] The beneficial effects of the above embodiments are that, based on the water body distribution range information, the water extraction range for the portion of the water body to be transferred to the disinfection tank is determined, thus ensuring the accuracy of water extraction and transfer from the sedimentation tank. Furthermore, based on the change in the contour characteristics of the top boundary of the sediment during the extraction process, this change can be, but is not limited to, changes in the clarity of the top boundary contour of the sediment. When the clarity of the line remains within a certain range, the current extraction flow rate for this portion of the water remains constant; when the clarity of the line gradually decreases, the extraction flow rate for this portion of the water is reduced. This avoids the simultaneous extraction of already settled substances into the disinfection tank during the extraction of this portion of the water.

[0091] In another embodiment, the colony analysis module is used to sample and analyze the effluent in the disinfection tank to obtain colony distribution characteristic information of the effluent, including:

[0092] Distributed sampling analysis was performed on the effluent from different locations inside the disinfection tank to obtain the colony concentration information corresponding to each location. The colony concentration information corresponding to the effluent from all locations was integrated and simulated to obtain the global colony concentration distribution information of the water body inside the disinfection tank.

[0093] The beneficial effects of the above embodiments are that distributed sampling analysis is performed on the effluent at different locations inside the disinfection tank to obtain the colony concentration information corresponding to each location of the effluent, and the colony concentration information corresponding to the effluent at all locations is integrated and simulated to obtain the global colony concentration distribution information of the water body inside the disinfection tank. This enables global quantitative identification of the colony concentration distribution inside the water body of the disinfection tank.

[0094] In another embodiment, the colony analysis module performs distributed sampling analysis on the effluent at different locations inside the disinfection tank to obtain colony concentration information for each location, including:

[0095] Step S1: Under aseptic conditions, take a certain amount of the sample to be tested and dissolve it in sterile water. Shake thoroughly until well mixed to prepare a sample solution. Dilute the sample solution using a 10-fold series of concentration gradient standards and dispense it into different test tubes. Inject or spread a quantitative amount of the dilution onto agar plates and incubate under the fixed temperature and time conditions specified in the standard to obtain colony plates. Count the number of colonies using electronic auxiliary equipment. Let N be... ci Let C be the colony count result of the i-th colony plate at a dilution factor of C. Then, the mean colony count of this sample at a dilution factor of C is:

[0096]

[0097] In the above formula (1), is the mean colony count of the sample at a dilution factor of C; m is the number of colony plates at a dilution factor of C; i is the colony plate number, which is an integer greater than or equal to 1 and less than or equal to m;

[0098] Step S2: Based on the calculation results of step S1 above, calculate the number of colonies obtained by dilution factor C of the sample. The calculation formula is as follows:

[0099]

[0100] In the above formula (2), N c This represents the number of colonies obtained from the sample after dilution by a concentration factor of C, where C is the dilution factor.

[0101] Step S3: Based on the calculation results of step S2 above, calculate the actual number of colonies in the sampled sample. The determination process is as follows:

[0102] If only one dilution plate has a colony count within the preset range, i.e., only one N... c If the value of N is between 30 and 300, then N c The value represents the total number of bacterial colonies in the sample.

[0103] If two consecutive dilutions have colony counts within the preset counting range, that is, if there are two N... c The value is between 30 and 300, denoted as N. c1 and N c2 The actual number of colonies in the sample is:

[0104]

[0105] in and These are the mean colony counts at dilution concentrations C1 and C2, respectively, with dilution concentration C1 being less than dilution concentration C2.

[0106] If the colony count on all dilutions is greater than 300, that is, all N... c If all values ​​are greater than 300, then the number of colonies on the plate with the highest dilution concentration is taken as the true number of colonies in the sample.

[0107] If the colony count on all dilutions is less than 30, that is, all N... c If all values ​​are less than 30, then the number of colonies on the plate with the highest dilution and lowest concentration is taken as the true number of colonies in the sample.

[0108] Based on the actual number of colonies, the colony concentration information corresponding to each location of the effluent is obtained.

[0109] The beneficial effects of the above embodiments are that, in colony analysis, it is necessary to perform distributed sampling analysis of the effluent at different locations within the disinfection tank to obtain the number of colonies corresponding to each location, thereby determining the colony concentration information for each location. Determining the colony count is crucial throughout the analysis process, as the result directly determines the arrangement and formulation of subsequent colony elimination control work, and has a decisive impact on the water quality of the effluent. Therefore, accurately measuring the colony count is critical in colony analysis. However, often due to excessive colonies in the sample, colony overlap occurs, making accurate colony counting impossible. Therefore, the sample is diluted. Different dilution factors also have a certain impact on the colony count measurement. To accurately measure the colony count and eliminate the influence of colony overlap and dilution on the colony count, further measures are needed. By performing a 10-fold serial standard dilution of the sampled sample and preparing multiple colony plates from the same dilution concentration, the number of colonies in multiple colony plates at the same dilution concentration is calculated, eliminating the impact of dilution on the accuracy of colony counting. At the same time, based on the colony count at multiple dilution concentrations, the true colony count of the sampled sample is comprehensively judged, thereby achieving accurate colony counting by eliminating the influence of colony overlap and colony dilution on the colony count.

[0110] In another embodiment, the colony analysis module performs distributed sampling analysis on the effluent at different locations inside the disinfection tank to obtain colony concentration information for each location, including:

[0111] Step A1: Take pictures of the tailwater at each location to obtain the corresponding tailwater image; perform visual recognition on the tailwater image to obtain the particle distribution information of the bacterial colonies in the tailwater; use the following formula (1) to obtain the average particle size of the particles formed by the bacterial colonies at the corresponding locations in the tailwater in the image dimension based on the edge position points of each bacterial colony.

[0112]

[0113] In the above formula (1), This represents the average particle size of the particles formed by the a-th colony in the tailwater at the k-th location along the image dimension; [X] k_a (p),Y k_a [p] represents the coordinates of the p-th edge point of the particle formed by the a-th colony in the tailwater at position k; B represents the set of edge point points of the a-th colony in the tailwater at position k; max p∈B [X k_a [p] represents the maximum x-coordinate of the edge position of the particle formed by the a-th colony in the tailwater at position k; max p∈B [Y k_a[p] represents the maximum ordinate value of the edge position point of the particle formed by the a-th colony in the tailwater at the k-th position; min p∈B [X k_a [p] represents the minimum x-coordinate of the edge position point of the particle formed by the a-th colony in the tailwater at position k; min p∈B [Y k_a [p] represents the minimum ordinate value of the edge position point of the particle formed by the a-th colony in the tailwater at the k-th position;

[0114] Step A2: Using formula (2) below, based on the position of the marked point in the tailwater image at each location and the average particle size of each colony formed in the tailwater along the image dimension, obtain the actual particle size of each colony in the tailwater at each location.

[0115]

[0116] In the above formula (2), D(k_a) represents the actual particle size of the a-th colony in the tailwater at the k-th position; (x1,y1) represents the coordinate value of the first marker point in the tailwater image at the k-th position; (x2,y2) represents the coordinate value of the second marker point in the tailwater image at the k-th position; and L represents the actual distance between the first marker point and the second marker point.

[0117] Step A3: Using the formula (3) below, based on the actual particle size of each colony in the effluent at each location and the average number of colonies per unit area, obtain the number of colonies in the effluent at each location.

[0118]

[0119] In the above formula (3), E(k) represents the number of colonies in the tailwater at the k-th position; S0 represents the unit area; E0 represents the average number of colonies per unit area; and A represents the total number of colonies in the tailwater at the k-th position.

[0120] The beneficial effects of the above embodiments are as follows: using the above formula (1), based on the edge position of each colony-forming particle, the average particle size of the colony-forming particles at the corresponding position in the tailwater in the image dimension is obtained, so that each colony is treated as a regular particle for analysis and calculation, which can improve the efficiency of subsequent calculations; then using the above formula (2), based on the position of the marker point in the tailwater image at each position and the average particle size of each colony-forming particle in the tailwater in the image dimension, the actual particle size of each colony in the tailwater at each position is obtained, so that the actual particle size of each colony is calculated based on the marker point, which is convenient for subsequent calculation of the number of colonies in the tailwater; then using the above formula (3), based on the actual particle size of each colony in the tailwater at each position and the average number of colonies per unit area, the number of colonies in the tailwater at each position is obtained, so that the colony concentration information corresponding to each position of the tailwater can be obtained based on the actual number of colonies.

[0121] In another embodiment, the colony elimination control module is used to adjust the delivery operation state of the disinfection gas to the disinfection tank according to the colony distribution characteristic information, including:

[0122] Based on the colony concentration distribution information, the entire water body inside the disinfection pool is divided into several low-colony-concentration water sub-regions and several high-colony-concentration water sub-regions. Based on the average colony concentration values ​​of each of the low-colony-concentration and high-colony-concentration water sub-regions, the ozone delivery flow rate and delivery duration are adjusted for each of the low-colony-concentration and high-colony-concentration water sub-regions.

[0123] The beneficial effects of the above embodiments are that, based on the colony concentration distribution information, the entire water body inside the disinfection tank is divided into several low-colony-concentration water body sub-regions and several high-colony-concentration water body sub-regions. Based on the average colony concentration values ​​of each of the low-colony-concentration and high-colony-concentration water body sub-regions, the ozone delivery flow rate and delivery duration are adjusted for each of the sub-regions. Generally speaking, the higher the average colony concentration value of the water body sub-region, the higher the corresponding ozone delivery flow rate and delivery duration. This allows for sufficient ozone sterilization treatment of the corresponding water body sub-regions, effectively improving the water quality of the effluent.

[0124] In summary, this intelligent wastewater treatment system for aquaculture adjusts the wastewater extraction operation based on the water circulation status of the aquaculture pond, thereby drawing the wastewater to a filtration pond. Visual monitoring of the filtration equipment in the filtration pond reveals its filtration status, allowing for adjustments to the filtration operation. The filtered wastewater is then transferred to a sedimentation pond, improving the effectiveness and thoroughness of filtration. Visual monitoring of the sedimentation pond further identifies water characteristics that can be transferred to a disinfection pond, adjusting the transfer operation to prevent sediment from being transferred. Finally, wastewater samples from the disinfection pond are analyzed to obtain bacterial distribution characteristics, adjusting the delivery of disinfectant gas to ensure overall disinfection efficiency while reducing disinfection time, effectively improving wastewater quality.

[0125] The above is only one specific embodiment of the present invention, and any improvements made based on the concept of the present invention shall be considered within the scope of protection of the present invention.

Claims

1. A smart wastewater treatment system for aquaculture, characterized in that, include: The tailwater extraction module is used to adjust the extraction operation state of the tailwater extraction from the aquaculture pond according to the water circulation state of the aquaculture pond, so as to extract the tailwater to the filtration pond. A filter visual recognition module is used to visually monitor the filtration equipment in the filter pool, obtain corresponding dynamic images of the filtration, and analyze the dynamic images of the filtration to determine the filtration status information of the filtration equipment. The filtration control module is used to adjust the filtration operation status of the filtration equipment according to the filtration status information, so as to transfer the filtered effluent to the sedimentation tank. A sedimentation visual recognition module is used to visually monitor the sedimentation tank, obtain dynamic images of sedimentation inside the sedimentation tank, and analyze the dynamic images of sedimentation to determine the water feature information corresponding to the portion of water inside the sedimentation tank that can be transferred to the disinfection tank. The water transfer control module is used to adjust the transfer operation status of the water body portion to the disinfection pool based on the water body characteristic information. The colony analysis module is used to sample and analyze the effluent in the disinfection tank to obtain the colony distribution characteristics of the effluent. The colony elimination control module is used to adjust the delivery operation status of the disinfection gas to the disinfection pool based on the colony distribution characteristic information. The filter visual recognition module is used to visually monitor the filtration equipment in the filter pool, obtain corresponding dynamic filtration images, and analyze the dynamic filtration images to determine the filtration status information of the filtration equipment, including: The filtration equipment in the filtration tank is dynamically photographed to obtain dynamic images of the filtration operation of the filtration equipment on the effluent; the dynamic images of the filtration operation are then processed into frames to obtain several filtration operation image frames. The image frame of the filtration operation is processed to obtain the average particle size of impurities in the effluent after filtration by the filtration device; the average particle size of impurities is compared with a preset particle size threshold. If the average particle size of impurities is greater than or equal to the preset particle size threshold, it is determined that the filtration device has not effectively filtered the effluent; otherwise, it is determined that the filtration device has effectively filtered the effluent. The colony analysis module is used to sample and analyze the effluent in the disinfection tank to obtain colony distribution characteristic information of the effluent, including: Distributed sampling analysis was performed on the effluent at different locations inside the disinfection tank to obtain the colony concentration information corresponding to each location of the effluent; the colony concentration information corresponding to the effluent at all locations was integrated and simulated to obtain the global colony concentration distribution information of the water body inside the disinfection tank. The colony analysis module performs distributed sampling and analysis on the effluent at different locations inside the disinfection tank to obtain the colony concentration information corresponding to each location of the effluent, including: Step A1: Take pictures of the tailwater at each location to obtain corresponding tailwater images; perform visual recognition on the tailwater images to obtain the particle distribution information of the bacterial colonies in the tailwater; and use the following formula (1) to obtain the average particle size of the particles formed by the bacterial colonies at the corresponding locations in the tailwater along the image dimension based on the edge position points of each bacterial colony. （1） In the above formula (1), Indicates the first The tailwater at the [position name] position The average particle size of a colony in the image dimension; Indicates the first The tailwater at the [position name] position The first particle formed by the colony The coordinates of each edge location point; Indicates the first The tailwater at the [position name] position A set of edge locations of a colony; Indicates the first The tailwater at the [position name] position The maximum x-coordinate value of the edge location point of the particle formed by the colony; Indicates the first The tailwater at the [position name] position The maximum value of the ordinate at the edge location of the particle formed by the colony; Indicates the first The tailwater at the [position name] position The minimum x-coordinate of the edge location point of the particle formed by the colony; Indicates the first The tailwater at the [position name] position The minimum vertical coordinate value among the edge points of particles formed by a colony; Step A2: Using the formula (2) below, based on the position of the marked point in the tailwater image at each location and the average particle size of each colony formed in the tailwater along the image dimension, obtain the actual particle size of each colony in the tailwater at each location. （2） In the above formula (2), Indicates the first The tailwater at the [position name] position The actual particle size of each colony; Indicates the first The coordinates of the first marker point in the tailwater image at each location; Indicates the first The coordinates of the second marker point in the tailwater image at each location; This represents the actual distance between the first and second marker points. Step A3: Using the formula (3) below, based on the actual particle size of each colony in the effluent at each location and the average number of colonies per unit area, obtain the number of colonies in the effluent at each location. （3） In the above formula (3), Indicates the first The number of bacterial colonies in the effluent at each location; Indicates unit area; This indicates the average number of colonies per unit area. Indicates the first The total number of bacterial colonies in the tailwater at each location.

2. The intelligent wastewater treatment system for aquaculture as described in claim 1, characterized in that: The tailwater extraction module is used to adjust the extraction operation state of tailwater extraction from the aquaculture pond according to the water circulation state of the aquaculture pond, thereby extracting the tailwater to the filtration pond, including: The flow rates of the input and output water in the aquaculture pond are obtained. Based on the flow rate difference between the input and output water flow rates, the maximum flow rate of wastewater that can be extracted from the aquaculture pond when the water depth inside the aquaculture pond is maintained within a preset depth range is estimated. Based on the maximum flow rate, the extraction flow rate of wastewater from the aquaculture pond is adjusted so that the wastewater is extracted to the filtration pond.

3. The intelligent wastewater treatment system for aquaculture as described in claim 1, characterized in that: The filtration control module is used to adjust the filtration operation state of the filtration equipment according to the filtration status information, thereby transferring the filtered effluent to a sedimentation tank, including: When the filtration device effectively filters the effluent, the filtration pump flow rate of the effluent is kept constant, thereby transferring the filtered effluent to the sedimentation tank. If the filtration device fails to effectively filter the effluent, the pumping flow rate of the filtration device for the effluent is reduced, thereby transferring the filtered effluent to a sedimentation tank.

4. The intelligent wastewater treatment system for aquaculture as described in claim 1, characterized in that: The sedimentation visual recognition module is used to visually monitor the sedimentation tank, obtain dynamic images of sedimentation inside the sedimentation tank, and analyze the dynamic images of sedimentation to determine the water feature information corresponding to the portion of water inside the sedimentation tank that can be transferred to the disinfection tank, including: The sedimentation tank is photographed with binoculars to obtain a dynamic binocular image of sedimentation inside the sedimentation tank; based on the binocular parallax of the dynamic binocular image of sedimentation, a corresponding dynamic three-dimensional image of sedimentation is generated. The dynamic three-dimensional image of the sedimentation is analyzed to obtain the top boundary contour feature information of the sediment inside the sedimentation tank; based on the top boundary contour feature information of the sediment, it is determined whether the water in the sedimentation tank is in a stable sedimentation state. When the water in the sedimentation tank is in a stable sedimentation state, the water distribution range information corresponding to the portion of the water inside the sedimentation tank that can be transferred to the disinfection tank is determined based on the top boundary contour feature information of the sediment.

5. The intelligent wastewater treatment system for aquaculture as described in claim 4, characterized in that: The water transfer control module is used to adjust the transfer operation status of the water body portion to the disinfection tank according to the water body characteristic information, including: Based on the water body distribution range information, the water body extraction range transferred to the disinfection tank is determined; and based on the change state of the top boundary contour feature information of the sediment during the extraction process of the water body, the extraction flow rate of the water body is adjusted.

6. The intelligent wastewater treatment system for aquaculture as described in claim 1, characterized in that: The colony elimination control module is used to adjust the delivery operation status of the disinfection gas to the disinfection pool according to the colony distribution characteristic information, including: dividing the global water body inside the disinfection pool into several low colony concentration water body sub-regions and several high colony concentration water body sub-regions according to the colony concentration distribution information; and adjusting the delivery flow rate and delivery duration of ozone to the low colony concentration water body sub-regions and the high colony concentration water body sub-regions based on the average colony concentration values ​​of the low colony concentration water body sub-regions and the high colony concentration water body sub-regions.

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