An automatic control system for sea cucumber cultivation

Abstract

The application relates to the technical field of water quality regulation, and provides an automatic control system for sea cucumber culture, which comprises a controller, and the controller is used for executing the following automatic control strategy: determining the activity degree of sea cucumber in a target period corresponding to various pollutants, obtaining the influence degree of the various pollutants on the growth of sea cucumber in combination with the change relation with the concentration fluctuation degree of the pollutants, obtaining the risk coefficient of the pollutants at each moment according to the concentration change speed and the concentration fluctuation degree of the pollutants at each moment, and finally obtaining the water quality deterioration index at each moment according to the risk coefficient and the influence degree, so that the influence degree of various pollutants in actual water quality on the growth of sea cucumber is analyzed, the accuracy of the water quality deterioration index is greatly improved, and the authenticity and accuracy of water quality judgment are improved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of water quality regulation, and particularly relates to an automatic control system for sea cucumber culture. BACKGROUND

[0002] The water quality of traditional sea cucumber culture relies on artificial regular sampling detection, and the data update frequency is low. It is difficult to capture water quality mutation (such as sudden drop of dissolved oxygen, ammonia nitrogen exceeding standard) in real time, which is easy to lead to sea cucumber anoxia death or disease outbreak. The existing system can accurately regulate water quality and maintain the optimal growth environment of sea cucumber by real-time monitoring of key parameters such as nitrogen and nitrite through sensors and automatically adjusting water exchange system and other equipment.

[0003] In the existing automatic control mode of sea cucumber culture, the water quality deterioration index at future time is usually predicted according to the water quality deterioration index at historical multiple time, such as using autoregressive moving average model for prediction. When the water quality deterioration index at future time meets the water quality deterioration condition, the water quality repair work is done in advance. In the process of obtaining the water quality deterioration index at each time, the existing technology is to judge whether the concentration of the most critical water pollutant reaches the preset threshold. If the concentration of the water pollutant reaches the preset threshold, the water quality is determined to be deteriorated. However, the water quality is determined only according to whether the concentration of one pollutant reaches the preset threshold, which will affect the authenticity and accuracy of water quality determination. SUMMARY

[0004] In order to solve the technical problem of inaccurate acquisition of existing water quality deterioration index, the purpose of the present application is to provide an automatic control system for sea cucumber culture, and the technical solution is as follows:

[0005] The present application provides an automatic control system for sea cucumber culture, comprising a controller, wherein the controller is used to execute the following automatic control strategy:

[0006] The activity degree of sea cucumber in the target period corresponding to each pollutant is determined, and the target period is obtained from the reference period at the current time;

[0007] Based on the change relationship between the activity degree and the concentration fluctuation degree of each pollutant in the corresponding target period, the influence degree of each pollutant on the growth of sea cucumber is obtained;

[0008] According to the concentration change rate of each target pollutant at each time in the reference period and the concentration fluctuation degree of each target pollutant in the target period, the risk coefficient of each target pollutant at each time is obtained. The target pollutant is the pollutant whose concentration at each time meets the preset condition;

[0009] Fusion said risk coefficient and said influence degree, combined with the number of target pollutants at each time proportion, get the water quality deterioration index at each time.

[0010] In an exemplary embodiment, the acquisition process of the activity level includes:

[0011] Acquire the moving distance of each sea cucumber in the aquaculture area in each target period corresponding to each pollutant;

[0012] Determine the difference between the moving distance and the preset normal moving distance, combined with the fluctuation of the moving distance of each sea cucumber in each target period corresponding to each pollutant, get the behavior abnormality degree of each sea cucumber in each target period corresponding to each pollutant;

[0013] According to the behavior abnormality degree and the maximum moving speed of sea cucumber in each target period corresponding to each pollutant, get the activity level of sea cucumber in each target period corresponding to each pollutant.

[0014] In an exemplary embodiment, the activity level of sea cucumber in each target period corresponding to each pollutant is obtained according to the behavior abnormality degree and the maximum moving speed of sea cucumber in each target period corresponding to each pollutant, including:

[0015] Acquire the average value of the behavior abnormality degree of all sea cucumbers in each target period corresponding to each pollutant;

[0016] Acquire the maximum moving distance in the moving distance of each sea cucumber in each target period corresponding to each pollutant, and obtain the maximum moving speed according to the maximum moving distance;

[0017] According to the average value of the behavior abnormality degree and the maximum moving speed, get the activity level of sea cucumber in each target period corresponding to each pollutant; the activity level is inversely related to the average value of the behavior abnormality degree, and is positively related to the maximum moving speed.

[0018] In an exemplary embodiment, the acquisition process of the target period includes:

[0019] Determine the target time of the candidate pollutant in the reference period; the target time is the time when the pollutant concentration of the candidate pollutant is lower than the safety threshold of the candidate pollutant and the concentration difference with the safety threshold of the candidate pollutant is less than the preset difference; the candidate pollutant is any kind of pollutant;

[0020] The target time which is continuous in time sequence constitutes the target period of the candidate pollutant.

[0021] In an exemplary embodiment, the acquisition process of the concentration fluctuation degree includes:

[0022] determining a number of concentration peaks of the candidate pollutant in any target period, a time interval between adjacent concentration peaks, and a concentration difference between the candidate pollutant and the safety threshold;

[0023] fusing the number of concentration peaks, the time interval, and the concentration difference to obtain a concentration fluctuation degree of the candidate pollutant in the any target period; the concentration fluctuation degree is positively correlated with the number of concentration peaks, and is negatively correlated with the time interval and the concentration difference.

[0024] In an exemplary embodiment, the change relationship is a change trend correlation.

[0025] The obtaining process of the influence degree comprises:

[0026] determining an average value of the activity degree of the sea cucumber in all target periods corresponding to various pollutants;

[0027] obtaining, according to the average value of the activity degree and the change trend correlation corresponding to various pollutants, an influence degree of various pollutants on the growth of the sea cucumber; the influence degree is negatively correlated with the average value of the activity degree, and is positively correlated with the change trend correlation.

[0028] In an exemplary embodiment, the obtaining process of the risk coefficient comprises:

[0029] obtaining, according to a concentration change rate of each target pollutant at any moment and a concentration fluctuation degree of the same target pollutant in the target period, a risk coefficient of each target pollutant at the any moment; the risk coefficient is positively correlated with the concentration change rate and the concentration fluctuation degree.

[0030] In an exemplary embodiment, the obtaining process of the water quality deterioration index comprises:

[0031] fusing the risk coefficient and the influence degree of various target pollutants at the any moment to obtain a water quality deterioration characteristic performance at the any moment;

[0032] obtaining, according to the water quality deterioration characteristic performance at the any moment and a number proportion of target pollutants at the any moment, a water quality deterioration index at the any moment; the water quality deterioration index is positively correlated with the water quality deterioration characteristic performance and the number proportion.

[0033] In an exemplary embodiment, after obtaining the water quality deterioration index at each moment, the automatic control strategy further comprises:

[0034] According to the water quality deterioration index of each time in the reference period, the water quality deterioration index of the next time of the current time is predicted.

[0035] When the water quality deterioration index of the next time meets the water quality deterioration condition, output the water changing instruction for the aquaculture.

[0036] In an exemplary embodiment, the target pollutant acquisition process comprises:

[0037] The pollutant at any time as the target time is determined as the target pollutant at the any time.

[0038] The present application has the following beneficial effects: The present application considers a large number of pollutants, and not only determines the water quality according to whether the concentration of a single pollutant reaches a preset threshold, but also combines the activity degree of sea cucumber under various pollutants and the change relationship between the concentration fluctuation degree of various pollutants to determine the influence degree of various pollutants on the growth of sea cucumber, and further combines the risk coefficient of various pollutants to determine the water quality deterioration index at each time, which can analyze the influence degree of various pollutants on the growth of sea cucumber actually existing, can avoid ignoring the overall water quality deterioration due to the concentration of a single pollutant, greatly improves the accuracy of the water quality deterioration index, and thus improves the authenticity and accuracy of the water quality determination. BRIEF DESCRIPTION OF DRAWINGS

[0039] Figure 1 is a module composition schematic diagram of an automatic control system for sea cucumber culture provided by an embodiment of the present application;

[0040] Figure 2 is a flowchart of an automatic control strategy corresponding to the automatic control system for sea cucumber culture provided by an embodiment of the present application;

[0041] Figure 3 is an acquisition flowchart of a target period provided by an embodiment of the present application;

[0042] Figure 4 is an acquisition flowchart of a concentration fluctuation degree provided by an embodiment of the present application;

[0043] Figure 5 is an acquisition flowchart of an activity degree provided by an embodiment of the present application;

[0044] Figure 6 is a specific implementation flowchart of step 17 provided by an embodiment of the present application;

[0045] Figure 7 is an acquisition flowchart of an influence degree provided by an embodiment of the present application;

[0046] Figure 8 is a flowchart of an acquisition process of a water quality deterioration index provided by one embodiment of the present application;

[0047] Figure 9 is a flowchart of a step process of an automatic control strategy corresponding to an automatic control system for sea cucumber culture provided by one embodiment of the present application. DETAILED DESCRIPTION

[0048] In order to further illustrate the technical means and effects adopted by the present application to achieve the predetermined purposes, the specific embodiments, structures, features and effects of the present application are described in detail below in combination with the drawings and preferred embodiments. In the following description, different "one embodiment" or "another embodiment" do not necessarily refer to the same embodiment. In addition, the specific features, structures or characteristics in one or more embodiments can be combined in any suitable form.

[0049] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which the present application belongs. The data information collected by the present application is obtained with full authorization.

[0050] The present embodiment provides an automatic control system for sea cucumber culture, which is used for automatically controlling the culture water in a sea cucumber culture area. The culture area can be a single culture area, or one of a plurality of culture areas obtained by dividing a large shallow pond by cofferdams and the like, and each culture area is independent and the culture water does not flow between each other. Each culture area is independently controlled.

[0051] The automatic control system for sea cucumber culture provided by the present embodiment includes a water quality pollutant detection device and a controller, wherein the water quality pollutant detection device is used for detecting various pollutants in the water quality in the culture area. Generally, the types of pollutants in the water quality in the culture area mainly include ammonia nitrogen, hydrogen sulfide, nitrite and the like, and accordingly, the water quality pollutant detection device includes an ammonia nitrogen concentration sensor, a hydrogen sulfide concentration sensor and a nitrite concentration sensor. As shown in the figure, the ammonia nitrogen concentration sensor, the hydrogen sulfide concentration sensor and the nitrite concentration sensor are connected with the controller. It should be understood that in addition to detecting the above three types of pollutants, other types of pollutants can also be detected according to the needs, and accordingly, other corresponding pollutant concentration sensors also need to be provided. Figure 1

[0052] ​The automatic control system for sea cucumber culture provided in this embodiment further comprises a camera, which is configured to acquire the motion state of each sea cucumber in the culture area. The installation position of the camera is set according to actual needs under the premise of ensuring that the motion state of each sea cucumber can be acquired. The camera can be installed directly above the water surface of the culture area and arranged towards the water surface, so that the entire culture area can be captured. In order to reduce the interference of water surface reflection and other factors, the camera can be placed at the bottom of the water in the culture area and arranged upwards. In this case, the camera needs to be configured as a waterproof camera. Moreover, the camera can be configured as a high-definition infrared camera to adapt to night monitoring. The camera acquires video images of the culture area in real time, identifies each sea cucumber individual in each frame of video through a target detection algorithm (such as YOLOv5), and then obtains the moving distance of each sea cucumber at adjacent two time points through trajectory tracking calculation or frame difference method.

[0053] The sampling frequencies of the ammonia nitrogen concentration sensor, the hydrogen sulfide concentration sensor, the nitrite concentration sensor, and the camera are set according to actual needs, such as once every 10 seconds. In an exemplary embodiment, the collected concentrations of various pollutants can be subjected to decimal scaling standardization processing to make them have similar scales and distributions, so as to better perform data processing. Decimal scaling standardization is a prior art, and the specific method is not described herein.

[0054] The controller can be a conventional control chip, such as a central processing unit (CPU). The controller can be connected with each sensor and the camera through wired connection or wireless connection. The controller receives the concentrations of various pollutants collected by the various pollutant concentration sensors and the video images collected by the camera, and performs data processing according to the received data information to execute the automatic control strategy as shown in Figure 2 The automatic control strategy comprises the following steps:

[0055] Step 1: determining the activity level of sea cucumber in the target period corresponding to each pollutant;

[0056] Step 2: obtaining the influence degree of each pollutant on the growth of sea cucumber based on the change relationship between the activity level and the concentration fluctuation degree of each pollutant in the corresponding target period;

[0057] Step 3: obtaining the risk coefficient of each target pollutant at each time point according to the concentration change speed of each target pollutant at each time point in the reference period and the concentration fluctuation degree of each target pollutant in the target period in which the target pollutant is located;

[0058] Step 4: fusing the risk coefficient and the influence degree, and combining the proportion of the number of target pollutants at each time point to obtain the water quality deterioration index at each time point.

[0059] The various steps are described in detail below in conjunction with the accompanying drawings.

[0060] Step 1: Determine the activity level of sea cucumber in the target period corresponding to various pollutants.

[0061] Sea cucumber prefers a stable growth environment. Even if the concentration of pollutants is within the safe range, frequent fluctuations will affect its feeding and metabolism. For example: the COD (Chemical Oxygen Demand) concentration fluctuates from 8 mg / L to 12 mg / L (both within the safety threshold of 15 mg / L) within a certain period of time, but the fluctuation range is as high as 4 mg / L, which will also cause sea cucumber to frequently adjust its physiological state and reduce growth efficiency; if the fluctuation range is less than 1 mg / L, it is considered stable.

[0062] For the current time, the reference period of the current time is obtained. In an exemplary embodiment, the current time is taken as the last time of its reference period, and the preset time length is taken as the time length of the reference period, thereby constituting the reference period of the current time. The preset time length is set by actual needs. In an exemplary embodiment, the preset time length is 100 time points, so the reference period of the current time is a period of 100 time points.

[0063] Since sea cucumber is sensitive to "fluctuations close to the safety threshold", even if it is not over-standard, the fluctuation itself will cause sea cucumber to be stressed (such as feeding stagnation and activity frequency drop). Therefore, for the time when the concentration of pollutants is close to the safety threshold, attention should be paid. Then, the target period corresponding to various pollutants is determined from the reference period of the current time. It should be understood that the safety threshold of different types of pollutants may be different, for example: the safety threshold of ammonia nitrogen is usually set to 0.5 mg / L, the safety threshold of hydrogen sulfide is usually set to 0.1 mg / L, and the safety threshold of nitrite is usually set to 0.1 mg / L.

[0064] In an exemplary embodiment, as shown in Figure 3 , a specific acquisition process of the target period is given:

[0065] Step 11: Determine the target time of the candidate pollutant in the reference period.

[0066] Since the target period of different types of pollutants in the reference period is different, in order to facilitate the description, taking any type of pollutant as an example, any type of pollutant is set as a candidate pollutant. The safety threshold of the candidate pollutant is defined as the candidate pollutant safety threshold.

[0067] It should be understood that the scenario applicable to the embodiment is that the concentration of each pollutant does not exceed the corresponding safety threshold. Since each pollutant is monitored in real time, when the concentration of a pollutant exceeds the corresponding safety threshold, the system will directly alarm and process, and the automatic control process provided by the embodiment will not be executed. Therefore, the pollutant concentration of the candidate pollutant at each time within the reference period is lower than the candidate pollutant safety threshold.

[0068] The concentration difference between the pollutant concentration of the candidate pollutant at each time and the candidate pollutant safety threshold is obtained. In an exemplary embodiment, the calculation method of the concentration difference is as follows:

[0069]

[0070] wherein, represents the concentration difference between the concentration of the wth pollutant at the ith time and the safety threshold of the wth pollutant, represents the concentration of the wth pollutant at the ith time, represents the safety threshold of the wth pollutant.

[0071] Taking the pollutant nitrite as an example, when the ambient temperature changes (such as suddenly clearing up after 3 consecutive rainy days) in sea cucumber culture water, the surface water temperature rises from 18°C to 23°C within a certain period of time, and the concentration of nitrite, which is originally stable at 0.06 mg / L, will rise due to the increased activity of nitrifying bacteria, and will approach the safety threshold. Even if the concentration of nitrite does not exceed the standard, the fluctuation of nitrite approaching the threshold will still cause the activity frequency of sea cucumbers to drop sharply.

[0072] The embodiment sets a preset difference, which is used to determine whether the concentration difference is large. The numerical range of the preset difference is 0-1, and the specific value is set according to the type of actual pollutant and the judgment required, and the preset difference of different types of pollutants can be different. In an exemplary embodiment, the preset difference is taken as an example.

[0073] The concentration difference between the pollutant concentration of the candidate pollutant at each time and the concentration difference of the candidate pollutant safety threshold is compared with the size of the preset difference, the concentration difference smaller than the preset difference is obtained, and the time corresponding to the concentration difference smaller than the preset difference is determined. These times are defined as target times. Thus, the target times of the candidate pollutant within the reference period are obtained.

[0074] Step 12: The target times that are continuous in time sequence constitute the target period of the candidate pollutant.

[0075] ​The target time periods of the candidate pollutant are defined as target time periods, and a plurality of target time periods are obtained as the target time periods of the candidate pollutant. It should be understood that the isolated target time is more likely to belong to noise data, and the isolated target time is not taken as a target time period.

[0076] Then, the concentration fluctuation degree of each pollutant in the corresponding target time period is obtained. Taking the candidate pollutant as an example, the target time periods of the candidate pollutant in the reference time period are determined, which are referred to as the target time periods of the candidate pollutant. The concentration fluctuation degree of the candidate pollutant in the target time period of the candidate pollutant is obtained. The concentration fluctuation degree represents the fluctuation of the concentration of the pollutant in the target time period. In an exemplary embodiment, as shown in Figure 4 The concentration fluctuation degree is obtained as follows:

[0077] Step 13: Determine the number of concentration peaks of the candidate pollutant in any target time period, the time interval between adjacent concentration peaks, and the concentration difference from the safety threshold of the candidate pollutant.

[0078] Taking any target time period of the candidate pollutant as an example, the concentration curve of the candidate pollutant in the target time period is obtained, and the number of peaks in the concentration curve is obtained. The peak indicates that the distance from the safety threshold is close, and the more the number of peaks, the more frequent the fluctuation of the concentration of the candidate pollutant near the safety threshold, the greater the concentration fluctuation degree of the candidate pollutant in the target time period, and the concentration fluctuation degree is positively correlated with the number of peaks.

[0079] The time interval between each two adjacent peaks in the concentration curve is obtained, and then the average value of the time interval between all adjacent peaks in the concentration curve is calculated as the peak time interval of the concentration curve. The smaller the peak time interval, the higher the frequency of the peaks in the concentration curve, the more intense the concentration fluctuation of the candidate pollutant in the target time period, the greater the concentration fluctuation degree of the candidate pollutant in the target time period, and the concentration fluctuation degree is inversely related to the peak time interval.

[0080] The average value of the concentration difference between the candidate pollutant and the safety threshold of the candidate pollutant in the target time period is calculated, and the smaller the average value of the concentration difference, the closer the concentration of the candidate pollutant in the target time period to the safety threshold, the more frequent the fluctuation of the concentration of the candidate pollutant near the safety threshold, the greater the concentration fluctuation degree of the candidate pollutant in the target time period, and the concentration fluctuation degree is inversely related to the average value of the concentration difference.

[0081] Step 14: Fuse the concentration peak number, time interval and concentration difference to obtain the concentration fluctuation degree of the candidate pollutant in any target time period.

[0082] The number of concentration peaks, the average of peak time interval and the average of concentration difference of the fusion candidate pollutant in the target time period are obtained, and the concentration fluctuation degree of the candidate pollutant in the target time period is obtained. Based on the above logic, a specific quantification method of the concentration fluctuation degree is as follows:

[0083]

[0084] wherein, represents the concentration fluctuation degree of the wth pollutant in the mth target time period, represents the number of peaks of the wth pollutant in the mth target time period, represents the total number of data points of the wth pollutant in the mth target time period, represents the proportion of the number of peaks of the wth pollutant in the mth target time period, represents the peak time interval of the wth pollutant in the mth target time period, and exp represents the exponential function with the natural constant as the base, represents the average of concentration difference of the wth pollutant in the mth target time period.

[0085] Thus, the concentration fluctuation degree sequence of the wth pollutant in each target time period is obtained: wherein, represents the concentration fluctuation degree of the wth pollutant in the first target time period, represents the concentration fluctuation degree of the wth pollutant in the second target time period.

[0086] Sea cucumbers are very sensitive to changes in water quality environment, especially to the concentration fluctuation of pollutants such as ammonia nitrogen, hydrogen sulfide and nitrite. If the concentration of these pollutants in water is too high, it will cause the sea cucumber to appear stress reaction, reduce the activity level, and even cause death. Since each pollutant has different effects on the growth of sea cucumber, it is necessary to first determine the activity level of sea cucumber in the target time period corresponding to each pollutant. In an exemplary embodiment, as shown in FIG. 2, a specific acquisition process of the activity level is as follows: Figure 5

[0087] Step 15: Obtain the moving distance of each sea cucumber in the breeding area in each target time period corresponding to each pollutant.

[0088] ​​For any sea cucumber in the cultivation area, take the jth sea cucumber as an example, determine the moving distance of the jth sea cucumber at each target moment in the mth target period of the wth pollutant. Wherein, the frame difference method is used to process the cultivation area images of adjacent two target moments, so as to identify each sea cucumber and the moving distance of each sea cucumber. The moving distance of the sea cucumber can be the distance between the center points of the sea cucumber regions in the cultivation area images of adjacent two target moments.

[0089] The moving distances of the jth sea cucumber at each target moment in the mth target period of the wth pollutant are arranged in time sequence to obtain the moving distance sequence of the jth sea cucumber in the mth target period of the wth pollutant. Then, the average value of the moving distances in the moving distance sequence of the jth sea cucumber in the mth target period of the wth pollutant is calculated as the average moving distance of the jth sea cucumber in the mth target period of the wth pollutant.

[0090] It should be understood that the period between the mth target period of the wth pollutant and its previous target period (i.e. the m-1th target period) is a period in which the concentration of the wth pollutant differs greatly from the safety threshold, i.e. a period in which the concentration of the wth pollutant is relatively normal. This period is defined as a normal period adjacent to the mth target period of the wth pollutant. Then, the moving distances of the jth sea cucumber at each moment in the normal period adjacent to the mth target period of the wth pollutant are obtained and arranged in time sequence to obtain the moving distance sequence of the jth sea cucumber in the normal period adjacent to the mth target period of the wth pollutant. Then, the average value of the moving distances in the moving distance sequence of the jth sea cucumber in the normal period adjacent to the mth target period of the wth pollutant is calculated as the average moving distance of the jth sea cucumber in the normal period adjacent to the mth target period of the wth pollutant, and the average moving distance of the jth sea cucumber in the normal period adjacent to the mth target period of the wth pollutant is set as the preset normal moving distance of the jth sea cucumber in the mth target period of the wth pollutant.

[0091] It should be understood that the analysis object of the present embodiment can be all sea cucumbers in the cultivation area, or selected sea cucumbers that are more active. The selected sea cucumbers that are more active can be sea cucumbers with an average moving distance greater than a preset threshold. In order to reduce errors, the present embodiment takes all sea cucumbers in the cultivation area as an example.

[0092] Step 16: Determine the difference between the moving distance and the preset normal moving distance, and combine the fluctuation of the moving distance of each sea cucumber in each target period corresponding to each pollutant to obtain the abnormality degree of each sea cucumber in each target period corresponding to each pollutant.

[0093] It should be understood that when the concentration of the pollutant is low, the sea cucumber is more active, and when the concentration of the pollutant is too high, the sea cucumber will show a less active state, and even stress, health damage or death. Therefore, the average moving distance of the jth sea cucumber in the mth target period of the wth pollutant is usually less than or equal to the corresponding preset normal moving distance. Then, the difference between the average moving distance of the jth sea cucumber in the mth target period of the wth pollutant and the corresponding preset normal moving distance, i.e. the difference between the average moving distance of the jth sea cucumber in the normal period adjacent to the mth target period of the wth pollutant, is obtained. The smaller the average moving distance of the jth sea cucumber in the mth target period of the wth pollutant is than the corresponding preset normal moving distance, the more abnormal the behavior of the jth sea cucumber in the mth target period of the wth pollutant is, i.e. the higher the abnormality degree of the behavior of the jth sea cucumber is.

[0094] In an exemplary embodiment, the absolute value of the difference between the average moving distance of the jth sea cucumber in the mth target period of the wth pollutant and the corresponding preset normal moving distance is calculated. The greater the absolute value of the difference, the more significant the influence of the fluctuation of the pollutant on the behavior of the sea cucumber, and the higher the abnormality degree of the behavior of the sea cucumber is.

[0095] The fluctuation of the moving distance of the jth sea cucumber in the mth target period of the wth pollutant is obtained. In an exemplary embodiment, the fluctuation is represented by a standard deviation. Therefore, the standard deviation of the moving distance of the jth sea cucumber in the mth target period of the wth pollutant is calculated. The greater the standard deviation, the greater the difference between the moving distances of the sea cucumber at different times, the more irregular the behavior of the sea cucumber is, and the higher the abnormality degree of the behavior of the sea cucumber is.

[0096] Taking the pollutant ammonia nitrogen as an example, when the concentration of ammonia nitrogen in the water body is stable and far from the safe threshold in the normal period, the physiological state of the sea cucumber is stable, the behaviors such as feeding and crawling are regular, the activity degree is high, and the moving distance is relatively stable and has small fluctuation. When the concentration of the pollutant is high, the sea cucumber is less active, and may have behavior disorder and irregularity due to stress. Such irregularity is the performance of the sea cucumber under stress due to the fluctuation of the pollutant “close to the safe threshold” (such as sometimes agitated and sometimes stagnant), which is in sharp contrast to the high activity degree and the relatively stable moving distance in the normal period. Therefore, the greater the difference between the moving distances in the target period and the normal period, the higher the abnormality degree of the behavior of the sea cucumber is.

[0097] Based on the above logic, a specific quantification method of the abnormality degree of the behavior is given as follows:

[0098] ;

[0099] wherein, represents the abnormality degree of the behavior of the jth sea cucumber in the mth target period of the wth pollutant, a standard deviation of the moving distance of the jth sea cucumber in the mth target period of the wth pollutant, a preset normal moving distance of the jth sea cucumber in the mth target period of the wth pollutant, i.e., an average of the moving distances of the jth sea cucumber in the normal periods adjacent to the mth target period of the wth pollutant, an average of the moving distances of the jth sea cucumber in the mth target period of the wth pollutant, norm represents a normalization function, such as a tanh function.

[0100] Through the above process, the abnormality degree of each sea cucumber in the mth target period of the wth pollutant is obtained.

[0101] Step 17: According to the abnormality degree and the maximum moving speed of the sea cucumber in the corresponding target period of each pollutant, the activity degree of the sea cucumber in the corresponding target period of each pollutant is obtained.

[0102] In an exemplary embodiment, as shown in Figure 6 a specific implementation process of step 17 is given as follows:

[0103] Step 171: Obtain the average of the abnormality degrees of all sea cucumbers in the corresponding target period of each pollutant.

[0104] The average of the abnormality degrees of all sea cucumbers in the mth target period of the wth pollutant is calculated, which is defined as the average of the abnormality degrees. The greater the average of the abnormality degrees, the lower the activity degree of the sea cucumber in the corresponding target period of each pollutant, and therefore, the activity degree is inversely related to the average of the abnormality degrees.

[0105] Step 172: Obtain the maximum moving distance in the moving distance of each sea cucumber in the corresponding target period of each pollutant, and obtain the maximum moving speed according to the maximum moving distance.

[0106] The maximum value, i.e., the maximum moving distance, is selected from the moving distances of each sea cucumber in the mth target period of the wth pollutant at each target time, as the maximum moving distance of all sea cucumbers in the mth target period of the wth pollutant. Since the moving distance is the moving distance of the sea cucumber between two adjacent time intervals, the ratio of the maximum moving distance to the time interval between the two adjacent time intervals is calculated as the maximum moving speed of the sea cucumber in the mth target period of the wth pollutant. It should be understood that if the time interval between the two adjacent time intervals is taken as a unit of time, the numerical value of the maximum moving speed of the sea cucumber in the mth target period of the wth pollutant is equivalent to the maximum moving distance of the sea cucumber in the mth target period of the wth pollutant. The greater the maximum moving speed, the more active the sea cucumber, and the higher the activity degree of the sea cucumber, and the two are positively related.

[0107] Step 173: Obtain the activity level of sea cucumber in each target time period corresponding to each pollutant according to the average value of the behavior abnormality degree and the maximum moving speed.

[0108] Based on the above logic, a specific quantification method of the activity level is given as follows:

[0109]

[0110] wherein, represents the activity level of sea cucumber in the mth target time period of the wth pollutant, represents the average value of the behavior abnormality degree of all sea cucumbers in the mth target time period of the wth pollutant, represents the maximum moving distance of sea cucumber in the mth target time period of the wth pollutant, which is equivalent to the maximum moving speed.

[0111] Thus, the activity level sequence of sea cucumber in each target time period of the wth pollutant is obtained as follows: wherein, represents the activity level of sea cucumber in the 1st target time period of the wth pollutant, represents the activity level of sea cucumber in the 2nd target time period of the wth pollutant.

[0112] Step 2: Obtain the influence degree of each pollutant on the growth of sea cucumber based on the change relationship between the activity level and the fluctuation degree of the concentration of each pollutant in the corresponding target time period.

[0113] The influence of the concentration fluctuation of a single target time period of pollutant on the activity level of sea cucumber can only reflect the correlation of local time, while the influence of the fluctuation of pollutant on the activity level of sea cucumber can be gradually accumulated. For example, the concentration peaks of pollutant in continuous several time periods can cause greater physiological stress to sea cucumber, so that its activity level decreases more obviously.

[0114] The change relationship between the activity level of sea cucumber in each target time period of the wth pollutant and the fluctuation degree of the concentration of the wth pollutant in each target time period is obtained, specifically, the change trend correlation between the activity level sequence of sea cucumber in each target time period of the wth pollutant and the fluctuation degree sequence of the concentration of the wth pollutant in each target time period is obtained. In an exemplary embodiment, the Pearson correlation coefficient of the activity level sequence and the fluctuation degree sequence is obtained, and the change trend correlation of the two is characterized by the Pearson correlation coefficient, the greater the Pearson correlation coefficient, the stronger the change trend correlation. It should be understood that, since the numerical range of the Pearson correlation coefficient is -1 to 1, in order to facilitate data processing, the Pearson correlation coefficient is normalized as follows: (1+Pearson correlation coefficient) / 2.

[0115] ​The greater the Pearson correlation coefficient between the activity level sequence and the concentration fluctuation degree sequence, the more relevant the change in activity level and the change in concentration fluctuation degree, the more significant the concentration change of the pollutant on the growth of sea cucumber, that is, the greater the impact degree on the growth of sea cucumber, the more attention needs to be paid to the concentration fluctuation of the pollutant, and the impact degree on the growth of sea cucumber and the change trend are positively correlated.

[0116] Based on the change trend correlation between the activity level sequence and the concentration fluctuation degree sequence, the impact degree of various pollutants on the growth of sea cucumber is obtained, and in an exemplary embodiment, as shown in Figure 7 , a specific acquisition process of the impact degree is given as follows:

[0117] Step 21: Determine the average activity level of sea cucumber in all target periods corresponding to various pollutants.

[0118] The average activity level of sea cucumber in each target period of the wth pollutant is calculated as the average activity level of sea cucumber in all target periods corresponding to the wth pollutant. The greater the average activity level, the less significant the impact of the concentration change of the pollutant on the growth of sea cucumber, that is, the smaller the impact degree on the growth of sea cucumber, and the impact degree on the growth of sea cucumber and the average activity level are inversely related.

[0119] Step 22: Obtain the impact degree of various pollutants on the growth of sea cucumber according to the average activity level and the change trend correlation corresponding to various pollutants.

[0120] Based on the above logical analysis, a specific quantification method of the impact degree is given as follows:

[0121] ;

[0122] wherein, represents the impact degree of the wth pollutant on the growth of sea cucumber, represents the average activity level of sea cucumber in all target periods corresponding to the wth pollutant, represents the normalized result of the Pearson correlation coefficient between the activity level sequence of sea cucumber in each target period of the wth pollutant and the concentration fluctuation degree sequence in each target period of the wth pollutant.

[0123] Through the above process, the impact degree of various pollutants on the growth of sea cucumber is obtained. The present embodiment also obtains the impact weight of various pollutants according to the impact degree of various pollutants on the growth of sea cucumber. The greater the impact degree, the more obvious the impact of the change of the pollutant on the growth of sea cucumber, and the more attention needs to be paid in the cultivation process, and the higher weight needs to be given.

[0124] Step 3: According to the concentration change rate of each target pollutant at each time in the reference period, and the concentration fluctuation degree of each target pollutant in the target period, the risk coefficient of each target pollutant at each time is obtained.

[0125] Firstly, the target pollutant at each time in the reference period is determined from various pollutants, and the target pollutant is the pollutant whose concentration at each time meets the preset condition. In an exemplary embodiment, for any time, the pollutant taking the time as the target time is determined, thereby obtaining several pollutants taking the time as the target time, and the several pollutants are taken as the target pollutant at the time. For example, it is assumed that there are four pollutants in total, and for the ith time, if the first pollutant and the third pollutant take the ith time as the target time, then the target pollutant of the ith time is the first pollutant and the third pollutant. In this way, the target pollutant at each time is obtained. It should be understood that the target pollutants at different times can be different, for example, the target pollutant of the (i+1)th time can be the first pollutant and the fourth pollutant.

[0126] The concentration change rate of each target pollutant at each time in the reference period is obtained. For the convenience of description, the nth target pollutant at the ith time is taken as an example. The concentration change rate of the nth target pollutant at the ith time is obtained. In an exemplary embodiment, the concentration of the nth target pollutant at the ith time is subtracted from the concentration at the (i-1)th time, and the obtained difference is divided by the concentration at the (i-1)th time, thereby obtaining the concentration change rate of the nth target pollutant at the ith time. It should be understood that the concentration change rate is essentially the concentration growth rate, and the concentration change rate can be positive, 0 or negative. The greater the value of the concentration change rate, the greater the growth amplitude of the target pollutant concentration, the greater the impact on the sea cucumber, and the higher the probability of exceeding the standard of the target pollutant, the greater the risk coefficient of the target pollutant, and the two are positively correlated.

[0127] Since the ith time is the target time of the nth target pollutant, the target period in which the ith time is located is obtained for the nth target pollutant, thereby obtaining the concentration fluctuation degree of the nth target pollutant in the target period in which the ith time is located. The greater the concentration fluctuation degree, the more unstable the concentration of the target pollutant, and the greater the risk coefficient of the target pollutant, and the two are positively correlated.

[0128] According to the concentration change rate of the nth target pollutant at the ith time and the concentration fluctuation degree of the nth target pollutant in the target period in which the ith time is located, the risk coefficient of the nth target pollutant at the ith time is obtained. When When greater than 0, it indicates that the target pollutant concentration is in a growth state, in which case, based on the above logical analysis, one specific quantification manner of the risk coefficient is given as follows:

[0129] ;

[0130] wherein, represents the risk coefficient of the nth target pollutant at the ith moment, represents the concentration fluctuation degree of the nth target pollutant in the target period at the ith moment, represents the concentration change rate of the nth target pollutant at the ith moment.

[0131] In addition, if is less than or equal to 0, it indicates that the target pollutant concentration is in a stable state or a downward trend, and the risk coefficient of the nth target pollutant at the ith moment is set to 0.

[0132] By using the above process, the risk coefficients of various target pollutants at various moments are obtained.

[0133] Step 4: Fusion of the risk coefficients and the influence degree, combined with the proportion of the number of target pollutants at each moment, to obtain the water quality deterioration index at each moment.

[0134] In the actual cultivation process of sea cucumbers, water quality deterioration is often the result of the joint action of multiple pollutants, for example, when ammonia nitrogen and nitrite are simultaneously in an upward trend, the toxicity of the two will be superimposed (ammonia nitrogen causes damage to the gills of sea cucumbers, and nitrite affects the oxygen-carrying capacity), and the harm to sea cucumbers is much greater than that of a single pollutant exceeding the standard, so the risk coefficient of the target pollutant at each moment and the influence degree of the target pollutant need to be comprehensively analyzed.

[0135] In an exemplary embodiment, as shown in Figure 8 , one specific acquisition process of the water quality deterioration index is given as follows:

[0136] Step 41: Fusion of the risk coefficients and the influence degree of various target pollutants at any moment to obtain the water quality deterioration characteristic performance at any moment.

[0137] In an exemplary embodiment, for each target pollutant at the i-th moment, the influence degree of the target pollutant on the growth of sea cucumber is obtained, and then the sum of the influence degrees of the target pollutants on the growth of sea cucumber at the i-th moment is calculated as the overall influence degree at the i-th moment. The influence degree of each target pollutant at the i-th moment is divided by the overall influence degree at the i-th moment, and the result is the influence weight of each target pollutant at the i-th moment. Through this calculation method, the influence weight of each target pollutant at the i-th moment is greater than 0 and less than 1, and the sum of the influence weights of each target pollutant at the i-th moment is 1. The greater the influence weight, the greater the influence of the fluctuation of the corresponding target pollutant on the growth state of the sea cucumber, and the more attention needs to be paid.

[0138] According to the influence weight of each target pollutant at the i-th moment, the risk coefficients of each target pollutant at the i-th moment are weighted and summed, and the result is the water quality deterioration characteristic performance at the i-th moment. The stronger the water quality deterioration characteristic performance, the higher the water quality deterioration index at the i-th moment, and the two are positively correlated.

[0139] Step 42: According to the water quality deterioration characteristic performance at any moment and the number proportion of target pollutants at any moment, the water quality deterioration index at any moment is obtained.

[0140] The number of species of target pollutants at the i-th moment is obtained, and the number of species of all pollutants detected in this embodiment is obtained. The ratio of the number of species of target pollutants at the i-th moment to the number of species of all pollutants is calculated as the number proportion of target pollutants at the i-th moment. The greater the number proportion of target pollutants, the higher the complexity of water quality, that is, the higher the water quality deterioration index, and the two are positively correlated.

[0141] According to the water quality deterioration characteristic performance at the i-th moment and the number proportion of target pollutants at the i-th moment, the water quality deterioration index at the i-th moment is obtained, and based on the above logical permission, a specific calculation method of the water quality deterioration index is given as follows:

[0142] ;

[0143] Wherein, represents the water quality deterioration index at the i-th moment, represents the number of species of target pollutants at the i-th moment, represents the number of species of all detected pollutants, represents the number proportion of target pollutants at the i-th moment, represents the influence weight of the n-th target pollutant at the i-th moment.

[0144] In this way, the water quality deterioration index of each time in the reference period of the current time is obtained, and the greater the water quality deterioration index, the worse the water quality.

[0145] Since the change of water quality is not an instant reaction, especially in the aquaculture system. For example, changes in dissolved oxygen, temperature or salinity in the water may take some time to be transmitted to the entire aquaculture area, and the feedback of the aquaculture area also has a certain lag. This means that even if it is found that some water quality parameters do not meet the standard, the effect of adjustment may be delayed to appear. Therefore, according to the water quality of the reference period of the current time, the water quality of the next time of the current time is predicted, and the regulation is performed in advance. Ensure that the sea cucumber grows in a suitable environment. In an exemplary embodiment, after obtaining the water quality deterioration index of each time, as shown in Figure 9 The automatic control strategy further comprises:

[0146] Step 5: According to the water quality deterioration index of each time in the reference period, the water quality deterioration index of the next time of the current time is predicted.

[0147] According to the water quality deterioration index of each time in the reference period of the current time, the water quality deterioration index sequence of the reference period is formed in time sequence. According to the water quality deterioration index sequence, the water quality deterioration index of the next time of the current time is predicted. This embodiment can use existing prediction algorithms, such as using an autoregressive moving average model, or using a deep learning algorithm (such as a multilayer perception, a recurrent neural network, a time convolution network, etc.). Thus, the water quality deterioration index of the next time of the current time is obtained.

[0148] Step 6: When the water quality deterioration index of the next time meets the water quality deterioration condition, output the water change instruction for aquaculture.

[0149] When the water quality deterioration index of the next time of the current time meets the water quality deterioration condition, specifically, a water quality deterioration threshold is preset, the value range of the preset water quality deterioration threshold is 0-1, and the specific value is set by actual judgment needs, for example, if a relatively safe judgment logic is required, the preset water quality deterioration threshold can be set to be relatively small, such as 0.6.

[0150] If the water quality deterioration index of the next time of the current time is greater than or equal to the preset water quality deterioration threshold, the water quality of the next time of the current time is deteriorated, and the water change instruction for aquaculture is output. Used to control the opening of the water change system, introduce qualified seawater or pretreated aquaculture water in advance, dilute or replace the existing aquaculture water, so as to reduce the pollutant concentration and ensure the suitability of the sea cucumber growth environment.

[0151] The embodiment is combined with various pollutant evaluation and data optimization, realizes maintenance on the water quality of the sea cucumber growth environment, considers system hysteresis and sea cucumber physiological characteristics, and improves the breeding effect.

[0152] It should be noted that the above-mentioned embodiment sequence of the application is only for description, and does not represent the advantages and disadvantages of the embodiment. The process depicted in the drawing does not necessarily require the specific order or continuous order shown to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or can be advantageous.

[0153] Each embodiment in the specification is described in a progressive manner, and the same or similar parts between each embodiment can be referred to each other, and each embodiment mainly explains the difference from other embodiments.

Claims

1. An automatic control system for sea cucumber farming, characterized in that, The controller is configured to execute an automatic control strategy as follows: Determine the activity level of the sea cucumber in the target period corresponding to each pollutant; the target period is obtained from the reference period at the current time; Based on the change relationship between the activity level and the concentration fluctuation degree of each pollutant in the corresponding target period, the influence degree of each pollutant on the growth of the sea cucumber is obtained; According to the concentration change rate of each target pollutant at each time in the reference period and the concentration fluctuation degree of each target pollutant in the target period, the risk coefficient of each target pollutant at each time is obtained; the target pollutant is the pollutant whose pollutant concentration at each time meets the preset condition; Fuse the risk coefficient and the influence degree, and combine the proportion of the number of target pollutants at each time to obtain the water quality deterioration index at each time.

2. The automatic control system for sea cucumber culture according to claim 1, wherein the control system is characterized in that, The acquisition process of the activity level includes: Obtain the moving distance of each sea cucumber in the target period corresponding to each pollutant in the cultivation area; Determine the difference between the moving distance and the preset normal moving distance, and combine the fluctuation of the moving distance of each sea cucumber in the target period corresponding to each pollutant to obtain the behavior abnormality degree of each sea cucumber in the target period corresponding to each pollutant; According to the behavior abnormality degree and the maximum moving speed of the sea cucumber in the target period corresponding to each pollutant, the activity level of the sea cucumber in the target period corresponding to each pollutant is obtained.

3. The automated control system for sea cucumber farming as described in claim 2, characterized in that, According to the behavior abnormality degree and the maximum moving speed of the sea cucumber in the target period corresponding to each pollutant, the activity level of the sea cucumber in the target period corresponding to each pollutant is obtained. The acquisition process of the target period includes: Determine the target time of the candidate pollutant in the reference period; the target time is the time when the pollutant concentration of the candidate pollutant is lower than the safety threshold of the candidate pollutant and the concentration difference with the safety threshold of the candidate pollutant is less than the preset difference; the candidate pollutant is any pollutant; The target time is continuous in time sequence to form the target period of the candidate pollutant.

4. The automatic control system for sea cucumber culture according to claim 1, wherein the control system is characterized in that, The acquisition process of the concentration fluctuation degree includes: Determine the number of concentration wave peaks of the candidate pollutant in any target period, the time interval between adjacent concentration wave peaks, and the concentration difference with the safety threshold of the candidate pollutant; ​ 5. An automated control system for sea cucumber farming as described in claim 4, characterized in that, ​ ​ Fusing the concentration peak number, the time interval and the concentration difference, a concentration fluctuation degree of the candidate pollutant in the any target period is obtained; the concentration fluctuation degree is positively correlated with the concentration peak number, and is negatively correlated with the time interval and the concentration difference.

6. The automatic control system for sea cucumber culture according to claim 1, wherein the control system is characterized in that, The change relationship is a change trend correlation; The obtaining process of the influence degree comprises: Determining an activity degree average of the sea cucumber in all target periods corresponding to various pollutants; According to the activity degree average and the change trend correlation corresponding to various pollutants, an influence degree of various pollutants on the growth of the sea cucumber is obtained; the influence degree is negatively correlated with the activity degree average, and is positively correlated with the change trend correlation.

7. The automatic control system for sea cucumber culture according to claim 1, wherein the control system is characterized in that, The obtaining process of the risk coefficient comprises: According to a concentration change rate of each target pollutant at any time and a concentration fluctuation degree of the same target pollutant in the target period, a risk coefficient of each target pollutant at the any time is obtained; the risk coefficient is positively correlated with the concentration change rate and the concentration fluctuation degree.

8. The automatic control system for sea cucumber culture according to claim 1, wherein the control system is characterized in that, The obtaining process of the water quality deterioration index comprises: Fusing the risk coefficient and the influence degree of various target pollutants at the any time, a water quality deterioration characteristic performance at the any time is obtained; According to the water quality deterioration characteristic performance at the any time and a quantity proportion of the target pollutant at the any time, a water quality deterioration index at the any time is obtained; the water quality deterioration index is positively correlated with the water quality deterioration characteristic performance and the quantity proportion.

9. The automatic control system for sea cucumber culture according to claim 1, wherein the system further comprises a computer program for controlling the system. After obtaining the water quality deterioration index at each time, the automatic control strategy further comprises: According to the water quality deterioration index at each time in the reference period, a water quality deterioration index of a next time of the current time is predicted; When the water quality deterioration index of the next time meets a water quality deterioration condition, a water changing instruction for aquaculture is output.

10. The automatic control system for sea cucumber culture according to claim 4, wherein the control system is characterized in that, The obtaining process of the target pollutant comprises: Determining a pollutant at any time as a target time as a target pollutant at the any time.

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