Dynamic regulation and control method and system for mung bean sprout cultivation water quality

Abstract

The invention relates to the technical field of water quality regulation and control, in particular to a mung bean sprout cultivation water quality dynamic regulation and control method and system.The mung bean sprout cultivation water quality dynamic regulation and control method comprises the following steps of collecting a rhizosphere and main water body conductivity time sequence, analyzing an extreme point lag difference, recognizing an absorption active stage, dynamically adjusting a pH set value and evaluating regulation and control response stability; a liquid injection trigger threshold value is optimized according to the conductivity slope ratio, and a water quality regulation and control result is output. According to the method, conduction delay between conductance signals can be recognized in real time by collecting rhizosphere liquid phase and main water body conductivity time sequence data and constructing change slope and lag difference data, and therefore the active absorption stage of the rhizosphere of the mung bean sprouts is extracted. A stable trend label can be constructed according to the judgment of the continuity and the change direction of the absorption stage, so that the regulation and control basis has more physiological correlation. In the aspect of pH control, a hydrogen ion concentration regulation target and exponential response logic are introduced to realize dynamic convergence of an acid-base balance control target, so that a regulation result is closer to an absorption state.

Description

Technical Field

[0001] The invention relates to the technical field of water quality regulation, and in particular to a method and system for dynamically regulating water quality in mung bean sprout cultivation. Background Art

[0002] The field of water quality control technology includes the whole process of measuring, analyzing and regulating various physical and chemical parameters in liquid environment, and is mainly used in industries with strict requirements on water environment quality, such as agricultural irrigation, food processing, and aquaculture. The core content of this technology is to monitor key indicators such as dissolved oxygen, pH value, conductivity, temperature, and ammonia nitrogen content in water in real time, and dynamically adjust the water quality in combination with the control system to keep the water environment in a suitable state.

[0003] Among them, the method for dynamic control of water quality in mung bean sprout cultivation refers to monitoring the changes in parameters such as conductivity and pH value in the hydroponic solution during the mung bean sprout seedling cultivation process, using a settable threshold range to determine water quality indicators, and collaboratively adjusting the solution concentration and acid-base balance through the water injection system, drainage pipeline and liquid adding components, thereby dynamically adjusting the composition and circulation method of the water used for seedling cultivation.

[0004] The existing technology uses the single-point change of conductivity and pH value as the basis for judgment, and adopts fixed thresholds to control rehydration and acid-base regulation, which lacks the ability to identify the dynamics of rhizosphere absorption at different growth stages of mung bean sprouts. Since it is impossible to extract the delayed change of conductivity between the rhizosphere and the main water body in real time, it is easy to cause untimely response to the peak of rhizosphere absorption, resulting in delayed nutrient supply or excessive regulation. In the process of adjusting pH, the response to the fluctuation trend of hydrogen ion concentration is not optimized, resulting in a deviation between the adjustment instruction and the actual absorption demand, causing a sharp fluctuation in the pH of the water body and increasing the risk of irritation to the root environment. In the monitoring of conductivity changes, a trend recognition mechanism has not been established based on continuous cycle data, resulting in the recognition of slow feedback of control measures relying on hysteresis performance, making it difficult to adjust the control parameters in time. In the feedback path of water quality regulation within the cycle, there is a lack of dynamic analysis support for standard deviation and coefficient of variation, and the evaluation of control effect lacks statistical stability basis, which poses a risk of misjudging the stability of the current water state. For example, the conductivity slope fluctuates during the continuous absorption active cycle. Summary of the invention

[0005] The purpose of the present invention is to solve the shortcomings of the prior art and to propose a method and system for dynamically regulating water quality in cultivating mung bean sprouts.

[0006] In order to achieve the above object, the present invention adopts the following technical scheme: a method for dynamically regulating water quality in cultivating mung bean sprouts, comprising the following steps: S1: Collect the change rate of the rhizosphere liquid-phase conductivity through an ion-selective electrode. Collect the conductivity changes in the rhizosphere and the main water body through the ion-selective electrode and convert them into corresponding time series respectively. Extract the extreme points of the time series and compare the timestamps, and output the conductivity change lag difference data; S2: Judge the stability of the conductivity change trend based on the conductivity change lag difference data of the previous cycle and the current cycle, and record it as the absorption active stage marking signal according to the judgment result; S3: Obtain the absorption active stage marking signal and judge the continuous occurrence state of the signal. Collect the current hydrogen ion concentration and adjust the set value of the hydrogen ion concentration based on the exponential target adjustment logic, and output the updated pH control result; S4: Based on the updated pH control result, collect the coefficient of variation of the pH change after execution within the current sampling cycle, and record the conductivity regulation response delay marking signal according to the coefficient of variation; S5: Based on the conductivity regulation response delay marking signal, collect the conductivity sampling data of three consecutive cycles, calculate the ratio with the slope of the water body conductivity change after the previous liquid injection, update the liquid injection trigger threshold setting according to the slope ratio, and output the water quality dynamic regulation result.

[0007] As a further solution of the present invention, the conductivity change lag difference data includes the derivative extreme point timestamp difference, the rhizosphere curve change characteristics, and the main water body curve response characteristics. The absorption active stage marking signal includes the continuous peak offset trend, the cycle trend stable state, and the time difference determination label. The updated pH control result is specifically the hydrogen ion concentration adjustment target, the pH control instruction set, and the liquid supplement pause state identifier. The conductivity regulation response delay marking signal includes the pH change abnormal index, the pH response stability evaluation parameter, and the deviation record state. The water quality dynamic regulation result specifically refers to the liquid injection trigger update instruction and the conductivity response correction.

[0008] As a further solution of the present invention, the specific steps for obtaining the conductivity change lag difference data are as follows: S111: Collect the change rate of the rhizosphere liquid-phase conductivity and the change rate of the main water body conductivity through an ion-selective electrode. Call the corresponding time series in the two types of conductivity data, rearrange the rhizosphere conductivity data and the main water body conductivity data respectively according to the time dimension based on the sampling time points, and generate conductivity time series curves for the two groups of data to obtain the rhizosphere and main water body time series curve data; S112: According to the rhizosphere and main water body time series curve data, calculate the first derivative of each curve at each sampling point respectively, smooth the obtained first derivative data sequences respectively, then detect the extreme points in the smoothed derivative sequences, and extract the position information of the derivative extreme points for the rhizosphere and main water body first derivative curves respectively to generate the rhizosphere and main water body derivative extreme point sets; S113: Call the set of derivative extreme points of the rhizosphere and the main water body, compare item by item according to the corresponding sampling time, extract the time stamp difference between the two derivative extreme points in each period, use the time delay difference in consecutive periods for cumulative recording, calculate the offset persistence parameter for each sampling period, and obtain the conductance change lag difference data.

[0009] As a further solution of the present invention, the steps for obtaining the absorption active stage marking signal are specifically as follows: S211: Call the conductance change lag difference data, extract the time delay difference between the derivative extreme points of the rhizosphere and the main water body in the previous period and the current period, judge the change direction of the difference between the two periods, identify whether there is a fluctuation reverse or mutation signal, and obtain the fluctuation state of the difference between periods; S212: According to the fluctuation state of the difference between periods, screen the period combinations in which the time difference directions in the two periods are the same and the amplitude change does not exceed the set offset ratio threshold, compare the delay difference of the current period with the absorption delay determination threshold, output the dual judgment results of trend continuity and amplitude satisfaction, and obtain the trend stability determination label; The offset ratio threshold is obtained by statistically calculating the relative change ratio of the time delay difference between the derivative extreme points of the rhizosphere and the main water body in multiple consecutive growth periods, calculating the change rate distribution of the difference between adjacent periods, and selecting the upper quartile of the change rate distribution sequence as the fluctuation tolerance boundary; The absorption delay determination threshold is obtained by collecting the time difference between the time points of the rhizosphere derivative peak and the main water body derivative peak in the mung bean sprout growth period, extracting the median of the delay difference samples during the stable absorption period, and using the median as the time determination benchmark for absorption effectiveness; S213: Call the trend stability determination label, judge whether the current period and the previous period simultaneously meet the dual judgment conditions. If it is in the established state, record the current period state as a specific stage label and output the absorption active stage marking signal.

[0010] As a further solution of the present invention, the steps for obtaining the updated pH control result are specifically as follows: S311: Call the absorption active stage marking signal, judge whether the signal is in the established state. If it is in the established state, generate a fluid infusion pause instruction and write the instruction into the water quality control logic interruption channel to obtain the fluid infusion interruption control result; S312: According to the fluid infusion interruption control result, keep the main water body conductivity control parameter unchanged and stop the current liquid injection operation, collect the hydrogen ion concentration in the current water body, calculate the deviation between the hydrogen ion concentration and the set pH target range, and obtain the hydrogen ion offset parameter data; S313: Invoke the hydrogen ion offset parameter data, construct a target concentration adjustment range based on the concentration offset direction and the current stable interval trend, perform exponential approximation adjustment in combination with the response curve, and generate an adjustment control instruction set to obtain the updated pH control result.

[0011] As a further solution of the present invention, the step of obtaining the conductance regulation response sluggishness marking signal is specifically as follows: S411: Based on the updated pH control result, collect the real-time pH detection value in the water body during the current sampling period and construct a time series data. Arrange the data according to the sampling frequency to form a continuous pH change sequence, calculate the standard deviation and average value of the continuous pH change sequence, and obtain the pH change coefficient of variation. S412: Judge the size relationship between the pH change coefficient of variation and the set pH stability threshold, obtain the difference between the pH value at the end of the current period and the upper and lower limits of the target pH range, and judge whether it is within the allowable deviation range. Summarize the two judgment results to generate a stable state determination label. The pH stability threshold is obtained by collecting the pH change data sequences of multiple periods during the mung bean sprout growth stage, calculating the coefficient of variation of the pH value in each period, screening the period samples with stable water absorption efficiency, and statistically obtaining the upper quartile of the coefficient of variation as the upper limit of the acceptable range of variation. S413: Invoke the stable state determination label to identify whether the current period state is a non-stable state identifier. If the label state is non-stable, establish a periodic response marking signal and write it into the water body regulation state registration record to generate a conductance regulation response sluggishness marking signal.

[0012] As a further solution of the present invention, the step of obtaining the water quality dynamic regulation result is specifically as follows: S511: Based on the conductance regulation response sluggishness marking signal, collect the main water body conductivity sampling data of the current period and the previous two periods, construct a conductivity change sequence in chronological order, calculate the conductivity change slope in each period of the conductivity change sequence, and obtain a continuous period conductivity slope sequence. S512: Invoke the continuous period conductivity slope sequence, extract the conductivity slope of the current period and the conductivity slope of the pre-injection reference period after the previous injection, calculate the ratio of the two, and judge the deviation of the ratio from the set conductance response adaptation threshold to obtain the ratio determination result of whether the conductance response of this period is adapted, and obtain the slope deviation determination label. The conductance response adaptation threshold is obtained by collecting the conductivity change slope sequences of the main water body before and after injection in multiple mung bean sprout growth periods, calculating the mean and standard deviation of the slope ratios in each period, screening the ratio distribution intervals of the normal water body response periods, and setting the upper limit of the interval. S513: Identify whether the response deviation status condition is satisfied according to the slope deviation determination tag. If satisfied, adjust the interval of the current liquid injection trigger threshold to form a new liquid injection trigger setting, synchronously update the liquid supplement rhythm in combination with the conductivity regulation strategy, and obtain the water quality dynamic regulation result.

[0013] A water quality dynamic regulation system for mung bean sprout cultivation, which is used to execute the above-mentioned water quality dynamic regulation method for mung bean sprout cultivation. The system includes: The conductivity change lag analysis module collects the change rate of the rhizosphere liquid phase conductivity through an ion selective electrode, collects the conductivity changes of the rhizosphere and the main water body through the ion selective electrode and converts them into corresponding time series respectively, extracts the extreme points of the time series and compares the timestamps, and outputs the conductivity change lag difference data; The absorption activity identification module judges the stability of the conductivity change trend based on the conductivity change lag difference data of the previous cycle and the current cycle, and records it as an absorption activity stage marking signal according to the judgment result; The pH dynamic regulation module obtains the absorption activity stage marking signal and judges the continuous occurrence state of the signal, collects the current hydrogen ion concentration and adjusts the hydrogen ion concentration set value based on the exponential target regulation logic, and outputs the updated pH control result; The regulation response monitoring module collects the coefficient of variation of the pH change after execution in the current sampling cycle based on the updated pH control result, and records the conductivity regulation response delay marking signal according to the coefficient of variation; The liquid injection trigger dynamic adjustment module collects the conductivity sampling data of three consecutive cycles based on the conductivity regulation response delay marking signal, calculates the ratio with the slope of the water body conductivity change after the previous liquid injection, updates the liquid injection trigger threshold setting according to the slope ratio, and outputs the water quality dynamic regulation result.

[0014] Compared with the prior art, the advantages and positive effects of the present invention are as follows: In the present invention, by collecting the time series data of the rhizosphere liquid phase and the main water body conductivity, constructing the change slope and lag difference data, the conduction delay between the conductivity signals can be identified in real time, so as to extract the active absorption stage of mung bean sprouts rhizosphere. According to the judgment of the persistence and change direction of the absorption stage, a stable trend label can be constructed to make the regulation basis more physiologically relevant. In terms of pH control, the hydrogen ion concentration regulation target and the exponential response logic are introduced to achieve the dynamic convergence of the acid-base balance control target, making the adjustment result closer to the absorption state and avoiding the water quality disturbance caused by frequent liquid supplementation. The calculation of the coefficient of variation of pH change is used as the evaluation basis for response stability, allowing the actual implementation stability of the regulation measures to be examined in addition to the control accuracy, and improving the robustness of the regulation feedback system. Further, by comparing the trends of the change slopes of the conductivity in consecutive cycles, the liquid injection trigger setting is dynamically updated to avoid misjudging the conductivity response lag period under a single threshold trigger, and enhancing the adaptability of the system to different absorption rate stages. Each execution step is organized through a timing logic to form a closed-loop control path, integrating four dimensions: absorption state recognition, pH adjustment, response stability evaluation, and threshold dynamic optimization, enhancing the perception and response efficiency of the rhizosphere-water interaction relationship during the seedling raising process, and achieving more precise dynamic water quality regulation. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] Figure 1 is a schematic diagram of the working process of the present invention; Figure 2 is a flowchart of step S1 of the present invention; Figure 3 is a flowchart of step S2 of the present invention; Figure 4 is a flowchart of step S3 of the present invention; Figure 5 is a flowchart of step S4 of the present invention; Figure 6 is a flowchart of step S5 of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0016] In order to make the objectives, technical solutions and advantages of the present invention clearer and more understandable, the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention.

[0017] In the description of the present invention, it should be understood that the orientation or positional relationship indicated by the terms "length", "width", "upper", "lower", "front", "rear", "left", "right", "vertical", "horizontal", "top", "bottom", "inner", "outer", etc. is based on the orientation or positional relationship shown in the drawings. It is only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and thus should not be construed as a limitation to the present invention. In addition, in the description of the present invention, the meaning of "a plurality of" is two or more, unless otherwise specifically defined.

[0018] Please refer to Figure 1 , the present invention provides a technical solution: a method for dynamically regulating the water quality for mung bean sprout cultivation, including the following steps: S1: Collect the change rate of the rhizosphere liquid-phase conductivity through an ion-selective electrode, and synchronously detect the change rate of the main water body conductivity. Convert the rhizosphere conductivity data and the main water body conductivity data into time-series curves respectively, calculate the first-order derivatives of the rhizosphere conductivity change curve and the main water body conductivity change curve, extract the extreme points of the rhizosphere and main water body derivative curves through a local maximum detection function, and based on the timestamp comparison, extract the time delay difference of the maximum points within the sampling period, and output the conductivity change lag difference data; S2: Judge the stability of the conductivity change trend based on the conductivity change lag difference data of the previous cycle and the current cycle. If the peak time points of the rhizosphere conductivity change rate in both cycles are earlier than the peak time points of the main water body conductivity change rate by a set time period, record the current cycle as the absorption active stage marker signal; S3: Obtain the absorption active stage marker signal and judge whether the signal continuously appears in two cycles. If the condition of continuously appearing in two cycles is met, call the control instruction to pause the water body replenishment action, keep the water body conductivity value maintained in the current state, collect the current hydrogen ion concentration, and adjust the hydrogen ion concentration set value based on the exponential target adjustment logic, and output the updated pH control result; S4: Based on the updated pH control result, collect the pH change curve after execution and calculate the coefficient of variation of the curve within the current sampling period. If the coefficient of variation is lower than the set pH stability threshold and within the range of deviation from the target pH value, keep the current injection threshold setting unchanged. If the coefficient of variation is higher than the set pH stability threshold, record the current cycle as the conductivity regulation response sluggish marker signal; S5: Based on the conductivity regulation response sluggish marker signal, collect the conductivity sampling data of three consecutive cycles, calculate the ratio with the slope of the water body conductivity change after the previous injection. If the ratio deviation exceeds the conductivity response adaptation threshold, update the injection trigger threshold setting, and output the water quality dynamic regulation result; The conductance change hysteresis difference data includes the derivative extreme point timestamp difference, the rhizosphere curve change characteristics, and the main water body curve response characteristics. The absorption active stage marker signals include the continuous peak shift trend, the stable state of the periodic trend, and the time difference determination label. The updated pH control result is specifically the hydrogen ion concentration regulation target, the pH control instruction set, and the fluid infusion pause state identifier. The conductance regulation response delay marker signals include the abnormal pH change index, the pH response stability evaluation parameter, and the deviation record state. The water quality dynamic regulation result specifically refers to the injection trigger update instruction and the conductance response correction.

[0019] Please refer to Figure 2 , and the specific steps for obtaining the conductance change hysteresis difference data are as follows: S111: Collect the rhizosphere liquid phase conductivity change rate and the main water body conductivity change rate through an ion-selective electrode, call the corresponding time series in the two types of conductivity data, rearrange the rhizosphere conductivity data and the main water body conductivity data respectively according to the time dimension based on the sampling time point, and generate a conductivity time series curve for the two sets of data to obtain the rhizosphere and main water body time series curve data; To collect the rhizosphere liquid phase conductivity change rate and the main water body conductivity change rate through an ion-selective electrode, data acquisition needs to be carried out based on the layout of the detection points. The detection points are set at the bottom of the culture tank and the center of the water body, and the sampling period is uniformly set to once every 10 seconds. During the collection process, record the time (representing the sampling time), the corresponding rhizosphere conductivity value (representing the conductivity of the rhizosphere region at time ) and the main water body conductivity value (representing the conductivity of the main water body region at time ), where the data within a certain period is, for example: , , , and so on. Next, it is necessary to sort the two sets of conductivity data respectively based on the sampling time point, and construct a time series curve for each group of timestamp-conductivity pairs . Taking the rhizosphere region as an example, construct , and for the main water body region, construct . During the implementation process, smooth the conductance data of each period through interpolation method and connect them into a continuous curve. For example, if linearly increases from 0.88 to 0.94 mS / cm within , then the curve of this period is shown as an upward smooth slope curve in the graph. This operation enables the original sampling point data to be converted into a time function expression that can be further used for derivative calculation and change trend analysis. Taking a sampling period covering 120 seconds as an example, each curve contains 12 groups of data points. After the above operations, the rhizosphere and main water body time series curve data can be finally obtained.

[0020] S112: Calculate the first derivatives of the two curves at each sampling point according to the rhizosphere and main water body time series curve data, perform smoothing processing on the obtained first derivative data sequences respectively, then detect the extreme points in the smoothed derivative sequences, extract the position information of the derivative extreme points for the rhizosphere and main water body first derivative curves respectively, and generate the rhizosphere and main water body derivative extreme point sets; According to the rhizosphere and main water body time series curve data obtained above 、 , it is necessary to calculate the first derivatives of the two curves at each sampling point respectively. The derivative is defined as the change in conductivity between two consecutive sampling points divided by the time difference, that is, the derivative value is , where represents the conductivity difference between two consecutive sampling points, represents the time interval between two sampling points. For example, if , , , then the first derivative is 0.003 mS / cm / s. Perform the above calculation operations on all sampling points in sequence to form the conductivity derivative sequences (representing the rhizosphere curve derivative) and (representing the main water body curve derivative). Since the on-site data may have jumps, it is necessary to perform smoothing processing on the derivative sequences. Here, the moving average method is adopted, and every three consecutive derivative values are averaged once. For example, for 、 、 , the smoothed value is 0.003. The smoothed derivative sequence is used to judge the position of the extreme points. It is necessary to compare each point with the adjacent two points. If the current value is greater than the two side points, it is regarded as a maximum value, otherwise it is a minimum value. Taking as an example, the third point 0.0025 is not an extreme point, and the fourth point 0.004 is a maximum value relative to the two sides. And so on, extract the positions of the respective extreme points of the rhizosphere and main water body in the time axis for the two groups of derivative sequences respectively, and form a set of point position information such as: 、 . Finally, obtain the rhizosphere and main water body derivative extreme point sets.

[0021] S113: Call the rhizosphere and main water body derivative extreme point sets, perform item-by-item comparison according to the corresponding sampling time, extract the time stamp difference between the two derivative extreme points in each period, use the time delay difference in consecutive periods for cumulative recording, calculate the offset persistence parameter of each sampling period, and obtain the conductance change lag difference data; Call the above rhizosphere and main water body derivative extreme point sets, and perform point position comparison according to the sampling time order. First, determine the start and end time periods of each period. For example, the first period is , the second period is , and the timestamps of the first maximum point or the dominant extreme point of the rhizosphere curve and the main water body curve are extracted in each period. For example, in the first period, the rhizosphere extreme value appears at , the main water body extreme value appears at , then the timestamp difference is 12 seconds. In the second period, they are 35 seconds for the rhizosphere and 49 seconds for the main water body respectively, and the difference is 14 seconds. Record the above timestamp differences and form a delay difference array: , then perform cumulative recording and dynamic update on this sequence to establish a change trend curve between periods. Assume that the current period delay difference is 14 seconds and the previous period is 12 seconds, then the trend is that the delay increases by 2 seconds. Continuing to track, it can be found whether the fluctuation range is stable. The judgment result is used as the input basis for the identification of the absorption active state in the subsequent stage, and finally the conductance change lag difference data is obtained.

[0022] Please refer to Figure 3 , and the steps for obtaining the absorption active stage marking signal are specifically as follows: S211: Invoke the conductance change lag difference data, extract the time delay difference between the rhizosphere and the main water body derivative extreme points in the previous period and the current period, judge the change direction of the difference between the two periods, identify whether there are fluctuation reverse or mutation signals, and obtain the difference fluctuation state between periods; Invoke the conductance change lag difference data. First, according to the conductance derivative change curves collected separately in the rhizosphere and the main water body regions, set the monitoring period to 24 hours, and extract the extreme points of the derivative change within each period, that is, the time point corresponding to the maximum derivative, denoted as the main water body derivative extreme time and the rhizosphere derivative extreme time , where represents the derivative peak moment in the main water body region, represents the derivative peak moment in the rhizosphere region, and the lag difference is obtained through the time difference between the two. Taking the samples of two consecutive periods as an example, if in period , , , the lag difference is 0.6 hours; in period , , , the lag difference is 0.2 hours, then the difference change between the two periods is , indicating that the delay of the rhizosphere response process relative to the main water body is shortened, and the change direction is judged to be decreasing. If the absolute value of this change amount is greater than the preset mutation determination threshold (for example, taking the average value of the difference changes in multiple periods as 0.18 hours and the standard deviation as 0.06 hours, then the mutation threshold can be set to ), a mutation signal is determined. The system records the obtained fluctuation state. For example, a reverse change is marked as "reverse", and a mutation is marked as "mutation". This state sequence is maintained in the data sequence for subsequent cycle screening and processing.

[0023] S212: According to the fluctuation state of the time difference between cycles, screen cycle combinations in which the time difference directions are the same and the amplitude change does not exceed the set offset ratio threshold in two cycles. Compare the delay difference of the current cycle with the absorption delay determination threshold, and output a dual judgment result of trend continuity and amplitude satisfaction to obtain a trend stability determination label; The offset ratio threshold is obtained by statistically calculating the relative change ratio of the time delay difference between the extreme value points of the derivatives in the rhizosphere and the main water body within multiple consecutive growth cycles, calculating the change rate distribution of the differences between adjacent cycles, and selecting the upper quartile of the change rate distribution sequence as the fluctuation tolerance boundary; The absorption delay determination threshold is obtained by collecting the time difference between the peak time points of the rhizosphere derivative and the peak time points of the main water body derivative during the mung bean sprout growth cycle, extracting the median of the delay difference samples during the stable absorption period, and using the median as the time determination benchmark for absorption effectiveness; According to the obtained cycle fluctuation state data, extract the lag difference in each pair of adjacent cycles, and record them as the current cycle delay difference , the previous cycle delay difference , and judge and whether the signs are the same. If the signs are the same, the directions are consistent. Then continue to calculate their relative amplitude change ratio. Define the change ratio as the difference between the current difference and the previous difference divided by the larger of their absolute values, that is , where is the change ratio, and are the delay differences of the two cycles. Taking an example, if , , then . If it is less than the set offset ratio threshold , it is considered that the fluctuation is within an acceptable range. This threshold is obtained by statistically calculating the change ratio of the delay differences in multiple consecutive cycles, calculating the change rate distribution, and selecting the upper quartile as the tolerance boundary. For example, if the sample ratio sequence is and the upper quartile is 0.165, then set . Screen cycle pairs that meet the requirements of the same direction and amplitude change not exceeding the threshold. Then compare the delay difference of the current cycle with the absorption delay determination threshold . This determination threshold is obtained based on the median of the delay samples during the stable absorption period of mung bean sprouts. For example, if the samples within ten cycles are and the median is 0.495 hours, it is set as , if it is marked as absorption effective. Finally, combining the two determination conditions, if the directions are the same and the amplitude change is satisfied, and the current delay difference satisfies the absorption effective condition, then the trend stability label "stable" is output; otherwise, it is marked as "unstable".

[0024] S213: Call the trend stability determination label to determine whether the current cycle and the previous cycle simultaneously satisfy the dual judgment conditions. If it is in the established state, record the current cycle state as a specific stage label and output the absorption active stage marking signal; Call the trend stability label data to determine whether the labels of the current cycle and the previous cycle are both "stable", denoted as the label variable , if , then set the absorption active state mark of the current cycle to 1, otherwise to 0, to form a state mark array . For example, if the trend label sequence is , then the corresponding mark array is , where "1" indicates that the cycle is determined to be in the absorption active stage, and its time, cycle number and other meta-information are recorded for growth rhythm modeling analysis, and finally a periodic absorption active mark output sequence is formed.

[0025] Please refer to Figure 4 , the specific steps for obtaining the updated pH control result are as follows: S311: Call the absorption active stage marking signal to determine whether the signal is in the established state. If it is in the established state, generate a fluid infusion pause instruction and write the instruction into the water quality control logic interrupt channel to obtain the fluid infusion interruption control result; When calling the absorption active stage marking signal, the system first reads the absorption active mark bit array , where represents the absorption active state mark bit of the th monitoring cycle. If the current cycle , that is, marked as "absorption active", then the judgment logic is "established state". After confirmation, a fluid infusion pause instruction is immediately generated. This instruction is implemented by setting the liquid injection interrupt bit in the control flag register to 1, and at the same time, this instruction signal is written into the control logic interrupt channel connected to the water quality regulation system. The control logic interrupt channel is a preset bidirectional communication buffer, and its bit mask is , representing the command channel corresponding to "fluid infusion pause". During the execution process, the specific action is to modify the value corresponding to the flag bit in the buffer register, changing it from the original state 0 to 1, forming a control interrupt signal flow, so that the fluid infusion equipment control system receives the task request of "pausing fluid infusion", and finally outputs the fluid infusion interruption control result as the active state 1. Taking an example, in the mung bean sprout culture solution monitoring system, when the absorption delay in the current cycle is 0.52 hours and the trend labels of two consecutive cycles are both "stable", corresponding to , the system then determines that the absorption enters the efficient stage, stops fluid infusion, sends a control command to the interrupt channel, and the system completes the fluid infusion interruption task.

[0026] S312: According to the fluid infusion interruption control result, keep the main water body conductivity control parameter unchanged and stop the current liquid injection operation, collect the hydrogen ion concentration in the current water body, calculate the deviation between the hydrogen ion concentration and the set pH target range, and obtain the hydrogen ion offset parameter data; According to the interrupt control result being in the "active" state, the system freezes the target value of the main water body conductivity in the current control parameters , where represents the target conductivity (unit: ), which is set to remain unchanged within the current cycle. Subsequently, the liquid injection operation is paused, and the hydrogen ion concentration monitoring unit is activated. The electrode probe collects the current hydrogen ion concentration value in the water body in real time , the system converts this value into a pH value, using the formula , where represents the dimensionless value of the water body acidity and alkalinity, represents the hydrogen ion concentration (unit: mol / L). Taking the main water body of mung bean sprouts as an example, if the currently collected hydrogen ion concentration is , then . Subsequently, the system reads the lower limit , upper limit of the set pH target range from the control database, calculates the deviation amount and determines the deviation direction. If the current value is less than the lower limit, it is on the low side, and the deviation amount is , indicating that the current pH deviates from the target lower limit, and the system records this deviation as the hydrogen ion offset parameter data.

[0027] S313: Call the hydrogen ion offset parameter data, construct the target concentration adjustment amplitude range according to the concentration offset direction and the current stable interval trend, perform exponential approach adjustment in combination with the response curve, and generate the adjustment control instruction set to obtain the updated pH control result; Call the hydrogen ion offset parameter data , where represents the minimum distance between the current pH and the target range. The system first judges the offset direction. If It represents a low state. Determine whether it is in a stable stage according to the current trend. If the trend label is "stable", activate the adjustment mechanism, construct the target concentration adjustment range, and set the pH correction target range to increase the current pH value to near the target lower limit value. For example, if the current value is 5.5 and the target is 5.8, the adjustment range is 0.3. Define the adjustment target increase as , and combine with the response curve to set the adjustment control function as the exponential approaching control method, and generate the control instruction set in the form of , where: represents the injection volume of the regulator at time (unit: mL), represents the upper limit of the maximum injectable regulator (unit: mL), is the approaching rate coefficient of exponential control (unit: ), represents the elapsed time from the start of the current adjustment cycle to the evaluation time (unit: minutes). Set , , and substitute it into the calculation at time to get: , generate the control instruction "Add 7.77 mL of pH regulator to the main water body", update the pH control result of the system to the adjusting state, record the current pH adjustment instruction and write it into the next cycle control sequence. This result indicates that the current water body pH is in a low state and needs to approach the target concentration range. The constructed control strategy has been quantified and generated according to the current offset and response speed. The advantage of the formula is that by introducing the approaching rate control factor and the product of the maximum injection volume produces a decreasing gain in the exponential function, making the injection volume of the regulator gradually approach the target value over time, avoiding overshoot, and making the adjustment response more stable and controllable.

[0028] Please refer to Figure 5 , and the specific steps for obtaining the conductance regulation response delay marking signal are as follows: S411: Based on the updated pH control result, collect the real-time pH detection value in the water body during the current sampling cycle and construct time series data. Arrange the data according to the sampling frequency to form a continuous pH change sequence, calculate the standard deviation and average value of the continuous pH change sequence, and obtain the pH change coefficient of variation; Based on the updated pH control result, first call the feedback instruction, the system starts the periodic data collection task, sets the single sampling cycle to 5 minutes, and the sampling interval is 1 time per minute, that is, a total of 5 data points are collected within the cycle, and construct the pH time series data , where represents the The pH value after subsampling (unit: dimensionless), the data obtained in a certain mung bean sprout hydroponic control experiment is as follows: The system arranges the sampled data to form a continuous pH change sequence and performs statistical analysis operations in sequence. First, the average value is calculated The calculation method is as follows: Here represents the number of samples, represents the th sampling value, is the sequence mean value (unit: dimensionless), reflecting the central tendency of the pH level within this period. Then, the standard deviation is calculated, and its calculation formula is as follows: The squared differences of each item are respectively: , , , , . The sum of the above items is , substituting into the formula gives: After obtaining the average value and the standard deviation , to further reflect the amplification effect of extreme deviations in the sequence on the fluctuation, a correction factor based on the maximum relative deviation is introduced in the calculation of the coefficient of variation, and the improved coefficient of variation of pH change is obtained: where: : The standard deviation of the current pH sequence, with the unit of dimensionless, : The pH mean value (unit: dimensionless), : The maximum deviation value in the sequence, : The corrected coefficient of variation of pH, with the unit of dimensionless. Calculate : , taking it as the maximum value and substituting into the calculation: , and finally the improved coefficient of variation of pH is obtained. This result is used to compare with the set pH stability threshold in the subsequent steps to judge the stability of the water body pH control state within the current period. The larger the value, the more significant the fluctuation, and vice versa, indicating that the pH change within the period is relatively stable. The advantage of the formula is that by introducing the maximum relative deviation correction to the standard coefficient of variation, it enhances the ability to reflect the influence of extreme data on the overall fluctuation, avoids the limitation that the standard deviation may mask single-point anomalies in short sequences, and is applicable to the fine-grained water body control scenario under high-frequency sampling.

[0029] S412: Compare the coefficient of variation of pH change with the set pH stability threshold, obtain the differences between the pH value at the end of the current cycle and the upper and lower limits of the target pH range, and determine whether they are within the allowable deviation range. Summarize the two judgment results to generate a stable state judgment label; The pH stability threshold is obtained by collecting the pH change data sequences of multiple cycles during the mung bean sprout growth stage, calculating the coefficient of variation of the pH value in each cycle, screening the cycle samples with stable water absorption efficiency, and statistically calculating the upper quartile of the coefficient of variation as the upper limit of the acceptable range of variation; The calculated pH coefficient of variation is compared with the set pH stability threshold The system calls the group of cycle samples marked as "stable absorption efficiency" in the historical data, calculates the corresponding coefficient of variation for each cycle and constructs an array of coefficients of variation. For example, select 5 sets of coefficients of variation in the sample set: , after sorting, the upper quartile is the 4th largest value, that is , this value is the maximum limit of acceptable fluctuation. Compare the of the current cycle with this threshold, and the judgment relationship is , it is concluded that the current variation exceeds the acceptable range and is marked as unstable fluctuation. Immediately afterwards, the system judges the relative difference between the pH value at the end of the cycle and the boundaries of the target pH range. Let the target pH range be , the last sampling value of the current cycle, , then: the difference from the lower limit , the difference from the upper limit . Determine whether it is within the allowable deviation range. Let the allowable absolute deviation threshold be , then both of the above two differences are less than , it is determined that the pH value is within the target tolerance interval. Finally, the system summarizes the two judgment results. If the coefficient of variation exceeds the limit but the pH value falls within the effective interval, it is still judged as "unstable" because the change process itself has deviated from the acceptable range, so the stable state judgment label for the current cycle is generated as "unstable".

[0030] S413: Call the stable state judgment label to identify whether the current cycle state is a non-stable state identifier. If the label state is non-stable, establish a cycle response marker signal and write it into the water body regulation state registration record, and generate a conductance regulation response delay marker signal; Call the stable state determination tag to identify whether the current period is in an "unstable" state. If the current tag is "unstable", the system confirms that the response action condition is met, immediately establishes a periodic response marker signal, and writes this signal as a record item into the response period sequence field in the regulation registration structure. The registration format is the period number, determination tag, trigger time, and response marker code. For example, if the current period number is T21, the trigger time is "12:35", and the response code is "R2", the record item is {T21, unstable, 12:35, R2}. After the recording is completed, the system generates a conductivity regulation response delay marker signal, and the marker content indicates that under the condition that the current pH fluctuation is not effectively controlled, it may have caused a lag response in the conductivity regulation link. This response process ensures that all unstable period states are tracked by the system and form a linkage feedback with the downstream control logic, which is used to enhance the traceability of water body management and the periodic consistency identification.

[0031] Please refer to Figure 6 , and the specific steps for obtaining the water quality dynamic regulation result are as follows: S511: Based on the conductivity regulation response delay marker signal, collect the main water body conductivity sampling data of the current period and the previous two periods, construct a conductivity change sequence in chronological order, calculate the conductivity change slope within each period in the conductivity change sequence, and obtain a continuous period conductivity slope sequence; Based on the conductivity regulation response delay marker signal, the system first determines whether there is a control response delay identifier in the current period . If it is in an established state, it enters the conductivity sampling analysis process and calls the current period , the previous period , and the main water body conductivity sampling data of the previous two periods . Set the sampling frequency within the period to once every 5 minutes, and the length of each period is 30 minutes. Then each period contains 6 equally spaced time points, denoted as , and the corresponding conductivity records are: the sampling value of the st period , the sampling value of the nd period , and the sampling value of the current th period . The system obtains the conductivity change rate of each period according to the linear trend of the conductivity sampling points in each period, and sets the slope within the period as , and its definition is: , where: : represents the conductivity change slope of the th period (unit: ), : the conductivity at the starting sampling point of the th period (unit: ), : Conductivity at the sampling point at the end of the th cycle (unit: ), : Represents the start and end times of the cycle, . Substituting the data and calculating gives: ; ; .

[0032] Finally, the conductivity change slope sequence for three consecutive cycles is obtained as: , which indicates that the response speed of the water body conductivity slows down cycle by cycle, and a response lag trend appears. In the subsequent steps, this sequence will be used to perform ratio operations and threshold judgments on the adaptability of the current cycle's conductivity regulation, providing a basis for regulation updates. The advantage of the formula is that through the parameter , the conductivity dynamic behavior of each cycle is transformed into a standard rate evaluation index, enabling the cycle response mode to be quantitatively modeled at the time series level and enhancing the recognition granularity of the control adjustment mechanism for the lag trend.

[0033] S512: Call the conductivity slope sequence of consecutive cycles, extract the conductivity slope of the current cycle and the conductivity slope of the pre - reference cycle after the previous liquid injection, calculate the ratio of the two, and perform a deviation judgment on the ratio with the set conductivity response adaptation threshold to obtain the ratio judgment result on whether the conductivity response of this cycle is adapted, and obtain the slope deviation judgment label; The conductivity response adaptation threshold is obtained by collecting the conductivity change slope sequence of the main water body before and after liquid injection during multiple mung bean sprout growth cycles, calculating the mean and standard deviation of the slope ratios in each cycle, screening the ratio distribution interval of the cycles with normal water body response, and setting it with the upper limit of the interval; After calling the conductivity slope sequence of consecutive cycles, the system sequentially extracts the conductivity change slope of the current cycle , and the slope calculated value in the pre - reference cycle. The reference cycle is the effective response cycle corresponding to the stable period after the previous liquid injection is completed. Let the cycle number be , and its corresponding sampling value is . Calculating the slope gives: . From this, the system calculates the ratio , which represents the adaptation degree of the current cycle response speed relative to the reference cycle, and is defined as: . Subsequently, call the conductivity response adaptation threshold set in the control system. This threshold is obtained based on historical sample statistics. The calculation process is: Collect the conductivity change slope ratio sequence , for example, the sampled value is , after sorting, the upper limit is the maximum normal value of 0.95, taken as , this value is the upper bound of the judgment range. If , it indicates that the current response rate is lower than the reference response lower limit, and there is an adaptation deviation. In this example, , the determination result is "deviation", and the system generates a slope deviation determination tag , indicating that the conductance response within this period does not meet the standard response conditions. Through the construction of the response ratio, the dynamic change of conductance can be compared with the standard period, effectively identifying the mismatch of the reaction regulation within the current control loop, and then guiding the subsequent threshold revision behavior.

[0034] S513: According to the slope deviation determination tag, identify whether the response deviation state condition is met. If it is met, adjust the interval of the current liquid injection trigger threshold to form a new liquid injection trigger setting, and synchronously update the liquid replenishment rhythm in combination with the conductance regulation strategy to obtain the water quality dynamic regulation result; According to the slope deviation determination tag , the system determines whether the current control state meets the deviation condition. If , the system triggers the adaptive update mechanism of the regulation parameters. First, call the current liquid injection trigger threshold setting value , which is defined as the amount of change in conductivity per unit time. When it is lower than this value, the next round of liquid injection behavior is started. The original setting is , the system re - sets a new trigger threshold according to the current deviation degree , the adjustment method is to lower the ratio part of the original value. According to the ratio significantly lower than , set the adjustment coefficient , then the corrected threshold is: , the system updates the control parameters, writes into the controller, and at the same time updates the adjustment rhythm parameter , which is defined as the minimum interval time of the unit liquid injection cycle. If the current rhythm is 20 minutes, set the extension adjustment amplitude minutes, then the new liquid injection rhythm is , the above - mentioned adjustment items are written into the liquid replenishment strategy table, and the liquid injection decision logic in the main water body control loop is synchronously updated. Finally, the system outputs a new regulation result, recording the current cycle , the adjusted threshold , the rhythm parameter , as well as the regulation response marker value and the deviation tag , which constitutes a set of water quality dynamic regulation parameters. The result shows that the current water body response lag has triggered the threshold adjustment and replenishment cycle reset mechanism, and subsequent replenishment will be executed with the newly set parameters. The advantage of the formula is that by quantitatively converting the deviation degree of the conductance rate into a dual adjustment amount of the threshold and rhythm, the periodic self-calibration of the system regulation sensitivity is achieved.

[0035] A water quality dynamic regulation system for mung bean sprout cultivation, which is used to execute the above-mentioned water quality dynamic regulation method for mung bean sprout cultivation. The system includes: The conductance change lag analysis module collects the change rate of the rhizosphere liquid-phase conductivity through an ion-selective electrode, collects the conductivity changes of the rhizosphere and the main water body through an ion-selective electrode and converts them into corresponding time series respectively, extracts the extreme points of the time series and compares the timestamps, and outputs the conductance change lag difference data; The absorption activity identification module judges the stability of the conductance change trend based on the conductance change lag difference data of the previous cycle and the current cycle, and records it as the absorption activity stage marking signal according to the judgment result; The pH dynamic regulation module obtains the absorption activity stage marking signal and judges the continuous appearance state of the signal, collects the current hydrogen ion concentration and adjusts the set value of the hydrogen ion concentration based on the exponential target regulation logic, and outputs the updated pH control result; The regulation response monitoring module collects the coefficient of variation of the pH change after execution within the current sampling cycle based on the updated pH control result, and records the conductance regulation response slow marking signal according to the coefficient of variation; The liquid injection trigger dynamic adjustment module collects the conductivity sampling data of three consecutive cycles based on the conductance regulation response slow marking signal, calculates the ratio with the slope of the water body conductivity change after the previous liquid injection, updates the liquid injection trigger threshold setting according to the slope ratio, and outputs the water quality dynamic regulation result.

[0036] The above is only the preferred embodiment of the present invention, and it does not limit the present invention in other forms. Any person skilled in the art may use the disclosed technical content to make changes or modifications into equivalent embodiments with equivalent changes and apply them to other fields. However, as long as it does not depart from the technical content of the technical solution of the present invention, any simple modification, equivalent change and modification made to the above embodiments based on the technical essence of the present invention still fall within the protection scope of the technical solution of the present invention.

Claims

1. A method for dynamically regulating the water quality in mung bean sprout cultivation, characterized in that, It includes the following steps: S1: Collect the change rate of rhizosphere liquid-phase conductivity through an ion-selective electrode, collect the conductivity changes in the rhizosphere and the main water body through the ion-selective electrode and convert them into corresponding time series respectively, extract the extreme points of the time series and compare the timestamps, and output the conductivity change lag difference data; S2: Judge the stability of the conductivity change trend based on the conductivity change lag difference data of the previous cycle and the current cycle, and record it as the absorption active stage marking signal according to the judgment result; S3: Obtain the absorption active stage marking signal and judge the continuous occurrence state of the signal, collect the current hydrogen ion concentration and adjust the set value of the hydrogen ion concentration based on the exponential target adjustment logic, and output the updated pH control result; S4: Based on the updated pH control result, collect the coefficient of variation of the pH change after execution in the current sampling cycle, and record the conductivity regulation response delay marking signal according to the coefficient of variation; S5: Based on the conductivity regulation response delay marking signal, collect the conductivity sampling data of three consecutive cycles, calculate the ratio with the slope of the water body conductivity change after the previous liquid injection, update the liquid injection trigger threshold setting according to the slope ratio, and output the water quality dynamic regulation result.

2. The method for dynamically regulating the water quality for mung bean sprout cultivation according to claim 1, wherein The conductivity change lag difference data includes the derivative extreme point timestamp difference, the rhizosphere curve change characteristics, and the main water body curve response characteristics. The absorption active stage marking signal includes the continuous peak offset trend, the cycle trend stability state, and the time difference determination label. The updated pH control result is specifically the hydrogen ion concentration adjustment target, the pH control instruction set, and the liquid supplement pause state identifier. The conductivity regulation response delay marking signal includes the pH change abnormal index, the pH response stability evaluation parameter, and the deviation record state. The water quality dynamic regulation result specifically refers to the liquid injection trigger update instruction and the conductivity response correction.

3. The method for dynamically regulating the water quality for mung bean sprout cultivation according to claim 1, wherein The specific steps for obtaining the conductivity change lag difference data are as follows: S111: Collect the rhizosphere liquid-phase conductivity change rate and the main water body conductivity change rate through an ion-selective electrode, call the corresponding time series in the two types of conductivity data, rearrange the rhizosphere conductivity data and the main water body conductivity data respectively according to the time dimension based on the sampling time points, and generate conductivity time series curves for the two groups of data to obtain the rhizosphere and main water body time series curve data; S112: According to the rhizosphere and main water body time series curve data, calculate the first derivative of the two curves at each sampling point respectively, perform smoothing processing on the obtained first derivative data sequences respectively, then detect the extreme points in the smoothed derivative sequences, and extract the derivative extreme point position information of the rhizosphere and main water body first derivative curves respectively to generate the rhizosphere and main water body derivative extreme point sets; S113: Call the rhizosphere and main water body derivative extreme point sets, compare them item by item according to the corresponding sampling time, extract the timestamp difference between the two derivative extreme points in each cycle, use the time delay difference in consecutive cycles for cumulative recording, calculate the offset persistence parameter of each sampling cycle, and obtain the conductivity change lag difference data.

4. The method for dynamically regulating the water quality for mung bean sprout cultivation according to claim 3, characterized in that, The specific steps for obtaining the absorption active stage marking signal are as follows: S211: Call the conductance change hysteresis difference data, extract the time delay difference between the rhizosphere and the main water body derivative extreme points in the previous cycle and the current cycle, judge the change direction of the difference between the two cycles, identify whether there is a fluctuation reverse or mutation signal, and obtain the difference fluctuation state between cycles; S212: According to the difference fluctuation state between cycles, screen the cycle combinations in which the time difference directions in the two cycles are the same and the amplitude change does not exceed the set offset ratio threshold, compare the delay difference in the current cycle with the absorption delay determination threshold, output the dual judgment results of trend continuity and amplitude satisfaction, and obtain the trend stability determination label; The offset ratio threshold is obtained by statistically analyzing the relative change ratio of the time delay difference between the rhizosphere and the main water body derivative extreme points in multiple consecutive growth cycles, calculating the change rate distribution of the difference between adjacent cycles, and selecting the upper quartile of the change rate distribution sequence as the fluctuation tolerance boundary; The absorption delay determination threshold is obtained by collecting the time difference between the rhizosphere derivative peak time point and the main water body derivative peak time point during the mung bean sprout growth cycle, extracting the median of the delay difference samples during the stable absorption period, and using the median as the time determination benchmark for absorption effectiveness; S213: Call the trend stability determination label, judge whether the current cycle and the previous cycle simultaneously meet the dual judgment conditions. If it is in the established state, record the current cycle state as a specific stage label and output an absorption active stage marking signal.

5. The method for dynamically regulating the water quality for mung bean sprout cultivation according to claim 4, characterized in that, The specific steps for obtaining the updated pH control result are as follows: S311: Call the absorption active stage marking signal, judge whether the signal is in the established state. If it is in the established state, generate a liquid supplement pause instruction and write the instruction into the water quality control logic interruption channel to obtain the liquid supplement interruption control result; S312: According to the liquid supplement interruption control result, keep the main water body conductivity control parameter unchanged and stop the current liquid injection operation, collect the hydrogen ion concentration in the current water body, calculate the deviation between the hydrogen ion concentration and the set pH target interval, and obtain the hydrogen ion offset parameter data; S313: Call the hydrogen ion offset parameter data, construct a target concentration adjustment amplitude interval according to the concentration offset direction and the current stable interval trend, perform exponential approach adjustment in combination with the response curve, and generate a regulation control instruction set to obtain the updated pH control result.

6. The method for dynamically regulating the water quality for mung bean sprout cultivation according to claim 5, wherein, The specific steps for obtaining the conductance regulation response sluggish marking signal are as follows: S411: Based on the updated pH control result, collect the real-time pH detection value in the water body during the current sampling cycle and construct time series data. Arrange the data according to the sampling frequency to form a continuous pH change sequence, calculate the standard deviation and average value of the continuous pH change sequence, and obtain the pH change coefficient of variation; S412: Judge the magnitude relationship between the pH change coefficient of variation and the set pH stability threshold, obtain the difference between the pH value at the end of the current cycle and the upper and lower limits of the target pH interval, and judge whether it is within the allowable deviation range. Summarize the two judgment results to generate a stable state determination label; The pH stability threshold is obtained by collecting a sequence of pH variation data over multiple cycles during the mung bean sprout growth stage, calculating the coefficient of variation of the pH value for each cycle, screening the cycle samples with stable water absorption efficiency, and statistically determining the upper quartile of the coefficient of variation as the upper limit of the acceptable range of variation. S413: Invoke the stable state determination tag to identify whether the current cycle state is a non-stable state identifier. If the tag state is non-stable, establish a cycle response marker signal and write it into the water body regulation status registration record, and generate a conductivity regulation response delay marker signal.

7. The method for dynamically regulating the water quality for mung bean sprout cultivation according to claim 6, characterized in that, The specific steps for obtaining the water quality dynamic regulation result are as follows: S511: Based on the conductivity regulation response delay marker signal, collect the main water body conductivity sampling data for the current cycle and the previous two cycles, construct a conductivity change sequence in chronological order, calculate the conductivity change slope for each cycle in the conductivity change sequence, and obtain a continuous cycle conductivity slope sequence. S512: Invoke the continuous cycle conductivity slope sequence, extract the conductivity slope of the current cycle and the conductivity slope of the pre-injection reference cycle after the previous injection, calculate the ratio of the two, and perform a deviation judgment on the ratio compared with the set conductivity response adaptation threshold to obtain the ratio judgment result of whether the conductivity response of this cycle is adapted, and obtain the slope deviation judgment tag. The conductivity response adaptation threshold is obtained by collecting a sequence of conductivity change slopes of the main water body before and after injection during multiple mung bean sprout growth cycles, calculating the mean and standard deviation of the slope ratios for each cycle, screening the ratio distribution interval of the cycles with normal water body response, and setting it as the upper limit of the interval. S513: According to the slope deviation judgment tag, identify whether the response deviation state condition is met. If it is met, adjust the current injection trigger threshold within an interval to form a new injection trigger setting, and synchronously update the liquid addition rhythm in combination with the conductivity regulation strategy to obtain the water quality dynamic regulation result.

8. A dynamic water quality regulation system for mung bean sprout cultivation, characterized in that, For the mung bean sprout cultivation water quality dynamic regulation method according to any one of claims 1-7, the system includes: The conductivity change lag analysis module collects the conductivity change rate of the rhizosphere liquid phase through an ion-selective electrode, collects the conductivity changes of the rhizosphere and the main water body through an ion-selective electrode and converts them into corresponding time series respectively, extracts the extreme points of the time series and compares the timestamps, and outputs the conductivity change lag difference data. The absorption active identification module judges the stability of the conductivity change trend based on the conductivity change lag difference data of the previous cycle and the current cycle, and records it as an absorption active stage marker signal according to the judgment result. The pH dynamic regulation module obtains the absorption active stage marker signal and judges the continuous occurrence state of the signal, collects the current hydrogen ion concentration and adjusts the hydrogen ion concentration set value based on the exponential target regulation logic, and outputs the updated pH control result. The regulation response monitoring module collects the coefficient of variation of the pH change after execution in the current sampling cycle based on the updated pH control result, and records the conductivity regulation response delay marker signal according to the coefficient of variation. The liquid injection trigger dynamic adjustment module collects the conductivity sampling data of three consecutive cycles based on the conductivity regulation response delay marker signal, calculates the ratio with the slope of the water body conductivity change after the previous liquid injection, updates the liquid injection trigger threshold setting according to the slope ratio, and outputs the water quality dynamic regulation result.

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