Full-automatic water ion concentration detection system based on AI technology

Abstract

The invention discloses a full-automatic water ion concentration detection system based on an AI technology, and particularly relates to the technical field of water quality detection. Comprising a water quality ion concentration detection area division module, a water quality ion concentration data acquisition module, an AI technical data analysis module, a water quality ion concentration detection evaluation module, a water quality ion concentration detection comprehensive analysis module and a water quality ion concentration detection man-machine interaction module. The water quality ion concentration detection area division module is used for taking water quality ions to be detected in a water environment as a target area and dividing the target area into a plurality of areas according to each water quality ion; by analyzing the dynamic parameters of the ion concentration of the water quality, the stable state conditions of the ion concentration in the water body in time and space can be detected, and the relatively high dynamic balance index is beneficial to improving the accuracy and reliability of the detection of the ion concentration of the water quality.

Description

Technical Field

[0001] The present invention relates to the technical field of water quality detection, and in particular to a fully automatic water quality ion concentration detection system based on AI technology. Background Art

[0002] AI technology stands for Artificial Intelligence, which is a new technical science that studies and develops theories, methods, technologies and application systems for simulating, extending and expanding human intelligence. Water quality safety is directly related to human health, ecological environment and economic development. With the continuous improvement of environmental protection awareness, the monitoring and evaluation of water quality has become increasingly important. In order to ensure water quality safety and protect water resources, AI technology has gradually been applied to the field of water environment monitoring, including environmental protection, industrial production, agricultural irrigation, drinking water safety, etc.

[0003] The ion concentration in water is one of the key indicators for measuring water quality, but traditional water quality ion concentration detection methods often have problems such as complex operation, long detection cycle, and limited accuracy, which makes it difficult to meet the needs of modern water quality monitoring. With the rapid advancement of industrialization and urbanization, water pollution problems are becoming increasingly serious, and accurate and timely monitoring of water quality is particularly important. In order to overcome the limitations of traditional water quality monitoring methods, automation and intelligent technologies are widely used in the field of water quality monitoring.

[0004] Therefore, the present invention proposes a fully automatic water quality ion concentration detection system based on AI technology to solve the above problems. Through advanced sensors and detection equipment, it can collect various ion concentration data in water quality in real time and accurately; then use the powerful data analysis and processing capabilities of AI to conduct in-depth analysis and modeling of these data, so as to quickly and accurately obtain the detection results of ion concentration without excessive human intervention, thereby improving detection efficiency and accuracy. At the same time, it has stronger adaptability and intelligence, can cope with various complex water quality conditions, and can continue to learn and optimize, and continuously improve detection performance as data accumulates. Summary of the invention

[0005] In order to overcome the above-mentioned defects of the prior art, an embodiment of the present invention provides a fully automatic water quality ion concentration detection system based on AI technology to solve the problems raised in the above-mentioned background technology.

[0006] To achieve the above-mentioned purpose, the present invention provides the following technical solutions: a fully automatic water quality ion concentration detection system based on AI technology, including a water quality ion concentration detection area division module, a water quality ion concentration data acquisition module, an AI technology data analysis module, a water quality ion concentration detection evaluation module, a water quality ion concentration detection comprehensive analysis module and a water quality ion concentration detection human-computer interaction module;

[0007] The water quality ion concentration detection area division module is used to take the water quality ions to be detected in the water environment as the target area, and divide it into a number of areas according to each water quality ion, which are sequentially recorded as 1, 2, 3, ..., i, ..., n;

[0008] The water quality ion concentration data acquisition module is used to collect water quality ion concentration data in the water environment through sensor technology, obtain and analyze various monitoring parameters of the fully automatic water quality ion concentration detection index, and output various monitoring parameters to the AI ​​technology data analysis module;

[0009] The AI ​​technology data analysis module includes a water quality ion concentration dynamic balance detection index analysis unit, a water quality ion concentration interaction index analysis unit, a water quality ion concentration spatial distribution characteristic index analysis unit, and a water quality ion concentration prediction index analysis unit, and outputs the analysis results of each analysis unit to the water quality ion concentration detection and evaluation module;

[0010] The water quality ion concentration detection and evaluation module is used to compare the fully automatic water quality ion concentration detection index obtained by the data analysis module with the set value, and output the comparison result to the water quality ion concentration detection comprehensive analysis module;

[0011] The water quality ion concentration detection comprehensive analysis module is used to comprehensively analyze the rationality factors calculated by the evaluation module, and output the comprehensive analysis results to the water quality ion concentration detection human-computer interaction module;

[0012] The water quality ion concentration detection human-computer interaction module is used to output the comprehensive detection index of water quality ion concentration transmitted by the comprehensive analysis module to the detection administrator information terminal.

[0013] Preferably, the monitoring parameters in the water quality ion concentration data acquisition module include detection administrator identity authentication information, water quality ion concentration dynamic parameters, water quality ion concentration interactive parameters, water quality ion concentration spatial distribution parameters and water quality ion concentration prediction parameters, wherein the water quality ion concentration dynamic parameters specifically include the current ion detection concentration value, the ion detection concentration value at the previous time point, the average ion detection concentration and the water quality flow rate; the water quality ion concentration interactive parameters specifically include the concentration of water quality ions, the coexisting ion concentration, the standard deviation of the pH value during water quality detection, the average pH value, the standard deviation of the water environment turbidity and the average water environment turbidity; the water quality ion concentration spatial distribution parameters specifically include the number of detection layers in the spatial distribution, the water quality ion concentration of each layer and the depth of water quality detection; the water quality ion concentration prediction parameters specifically include the average ion concentration during the water quality ion concentration detection, the water quality ion concentration in the same period of the past three years and the water quality ion concentration detected in the most recent period.

[0014] Preferably, the model for obtaining the water quality ion concentration dynamic balance detection index in the water quality ion concentration dynamic balance detection index analysis unit is:

[0015]

[0016] Among them Cdei i It represents the dynamic balance detection index of the ion concentration of the i-th water quality, C 2 Indicates the current ion detection concentration value, C 1 Indicates the ion detection concentration value at the previous time point, Max indicates the maximum value, C 0 represents the average value of the ion detection concentration within the time interval, v s represents the water mass flow rate, and λ represents the ambient temperature adjustment coefficient.

[0017] Preferably, the model for obtaining the water quality ion concentration interaction index in the water quality ion concentration interaction index analysis unit is:

[0018]

[0019] Among them Wcii i Represents the interactive index of the ion concentration of the i-th water quality, Ic i Represents the concentration of the i-th water ion, (Cic) i It represents the concentration of coexisting ions that interact with the i-th water quality ion, PH_b represents the standard deviation of the pH value of the water environment during the water quality detection period, PH_p represents the average pH value of the water environment, NTU_b represents the standard deviation of the turbidity of the water environment during the water quality detection period, and NTU_p represents the average turbidity of the water environment.

[0020] Preferably, the model for obtaining the water quality ion concentration spatial distribution characteristic index in the water quality ion concentration spatial distribution characteristic index analysis unit is:

[0021]

[0022] Among them Sdhi i represents the spatial distribution characteristic index of the ion concentration of the i-th water quality, L represents the number of detection layers of the spatial distribution, Ic i l represents the concentration of the i-th water ion in the l-th layer, Ic i l represents the concentration of the i-th water ion in the l+1 layer, d l+1 represents the depth of the l+1th layer, d l Indicates the depth of layer l.

[0023] Preferably, the model for obtaining the water quality ion concentration prediction index in the water quality ion concentration prediction index analysis unit is:

[0024]

[0025] Icpi i Ic represents the prediction index of the ion concentration of the i-th water quality, p Indicates the average value of ion concentration during water quality ion concentration detection, Ic b Indicates the standard deviation of water ion concentration in the same period of the past three years, Ic M Indicates the ion concentration at the Mth time in the past, Ic 0 Indicates the current ion concentration, M indicates the value in the most recent period, and M is smaller than the value during the water quality ion concentration detection period.

[0026] Preferably, the water quality ion concentration detection and evaluation module includes the following steps:

[0027] Step 1: The water quality ion concentration dynamic balance detection index analysis calculation result Cdei obtained in the water quality ion concentration dynamic balance detection index analysis unit i Substituting into the formula: Where γ(Cdei i ) represents the rationality factor of the dynamic balance detection index of water quality ion concentration, Cdei 0 Indicates the set value;

[0028] Step 2: Obtain the water quality ion concentration interaction index analysis calculation result Wcii from the water quality ion concentration interaction index analysis unit i Substituting into the formula: Where γ(Wcii i ) represents the rationality factor of the interaction index of water quality ion concentration, Wcii 0 Indicates the set value;

[0029] Step 3: Obtain the water quality ion concentration spatial distribution characteristic index analysis calculation result Sdhi from the water quality ion concentration spatial distribution characteristic index analysis unit i Substituting into the formula: Where γ(Sdhi i ) represents the rationality factor of the spatial distribution characteristic index of water quality ion concentration, Sdhi 0 Indicates the set value;

[0030] Step 4: Obtain the water quality ion concentration prediction index analysis calculation result Icpi from the water quality ion concentration prediction index analysis unit i Substituting into the formula: Where γ(Icpi i ) represents the rationality factor of water quality ion concentration prediction index, Icpi 0 Indicates the set value.

[0031] Preferably, the comprehensive analysis model in the water quality ion concentration detection comprehensive analysis module is:

[0032]

[0033] Among them, Icci represents the comprehensive detection index of water quality ion concentration, and n represents the number of water quality ion types.

[0034] Technical effects and advantages of the present invention:

[0035] 1. The present invention can detect the stable state of ion concentration in water in time and space by analyzing the dynamic parameters of water quality ion concentration. When the ion concentration in water is in dynamic equilibrium, it means that its concentration fluctuates within a certain range but remains stable overall. A higher dynamic equilibrium index helps to improve the accuracy and reliability of water quality ion concentration detection;

[0036] 2. The present invention can detect the interaction between different ions and accurately measure the concentration of various ions in water by analyzing the interaction parameters of water quality ion concentration. By comprehensively considering factors such as the main ion concentration, coexisting ion concentration, pH value and turbidity, the interaction between different ions and its impact on the overall water quality can be more accurately understood;

[0037] 3. The present invention can detect the spatial distribution differences of ion concentration by analyzing the spatial distribution parameters of water quality ion concentration. If only part of the area is detected, the changes in ion concentration in other areas may be ignored, resulting in incomplete and inaccurate detection results. Therefore, it is necessary to fully consider the influence of spatial distribution characteristics to improve the accuracy of detection. BRIEF DESCRIPTION OF THE DRAWINGS

[0038] Figure 1 It is a schematic diagram of the overall process of the present invention. DETAILED DESCRIPTION

[0039] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0040] See also Figure 1 As shown, the present invention provides a fully automatic water quality ion concentration detection system based on AI technology, including a water quality ion concentration detection area division module, a water quality ion concentration data acquisition module, an AI technology data analysis module, a water quality ion concentration detection evaluation module, a water quality ion concentration detection comprehensive analysis module and a water quality ion concentration detection human-computer interaction module.

[0041] The water quality ion concentration detection area division module is connected to the water quality ion concentration data acquisition module, the AI ​​technology data analysis module is respectively connected to the water quality ion concentration detection and evaluation module and the water quality ion concentration data acquisition module, the water quality ion concentration detection comprehensive analysis module is respectively connected to the water quality ion concentration detection and evaluation module and the water quality ion concentration detection human-computer interaction module, and the water quality ion concentration detection human-computer interaction module is respectively connected to the water quality ion concentration detection and evaluation module and the AI ​​technology data analysis module.

[0042] The water quality ion concentration detection area division module is used to take the water quality ions to be detected in the water environment as the target area, and divide it into several areas according to each water quality ion, which are sequentially recorded as 1, 2, 3, ..., i, ..., n, and each water quality ion includes but is not limited to: for example, calcium ion Ca 2 +、Magnesium ion Mg 2+ 、Sodium ion Na + wait;

[0043] The water quality ion concentration data acquisition module is used to collect water quality ion concentration data in the water environment through sensor technology, obtain and analyze various monitoring parameters of the fully automatic water quality ion concentration detection indicators, and output various monitoring parameters to the AI ​​technology data analysis module. Its data acquisition includes the following steps:

[0044] Step 1: The water sample collection unit uses a water quality sampler to automatically collect water samples from the water source to be tested, including water samples at different depths;

[0045] Step 2: Water sample pretreatment unit: Use filtering technology and digestion technology to filter and digest the collected water samples to remove impurities and interfering substances, providing good conditions for subsequent detection;

[0046] Step 3: Water quality ion concentration collection unit: Use advanced sensors and detection technology to detect the concentrations of various ions in the pre-treated water samples, and obtain and analyze the various monitoring parameters of the fully automatic water quality ion concentration detection indicators;

[0047] What needs to be specifically explained in this embodiment is the use of highly sensitive ion-selective electrodes or optical sensors to detect specific ions in water (such as calcium, magnesium, sodium, potassium, chlorine, etc.), which can continuously collect data to ensure real-time performance.

[0048] What needs to be specifically explained in this embodiment is that various monitoring parameters include detection administrator identity authentication information, water quality ion concentration dynamic parameters, water quality ion concentration interactive parameters, water quality ion concentration spatial distribution parameters and water quality ion concentration prediction parameters, among which the water quality ion concentration dynamic parameters are specifically the current ion detection concentration value, the ion detection concentration value at the previous time point, the average ion detection concentration and the water quality flow rate; the water quality ion concentration interactive parameters are specifically the concentration of water quality ions, the coexisting ion concentration, the standard deviation of the pH value during the water quality detection period, the average pH value, the standard deviation of the water environment turbidity and the average water environment turbidity; the water quality ion concentration spatial distribution parameters are specifically the number of detection layers in the spatial distribution, the water quality ion concentration of each layer and the depth of water quality detection; the water quality ion concentration prediction parameters are specifically the average ion concentration during the water quality ion concentration detection period, the water quality ion concentration in the same period of the past three years and the water quality ion concentration detected in the most recent period.

[0049] The AI ​​technology data analysis module includes a water quality ion concentration dynamic balance detection index analysis unit, a water quality ion concentration interaction index analysis unit, a water quality ion concentration spatial distribution characteristic index analysis unit, and a water quality ion concentration prediction index analysis unit, and outputs the analysis results of each analysis unit to the water quality ion concentration detection and evaluation module. The data analysis includes the following steps:

[0050] What needs to be specifically explained in this embodiment is that the water quality ion concentration dynamic balance detection index analysis unit is used to calculate the dynamic parameters of water quality ion concentration, the water quality ion concentration interaction index analysis unit is used to calculate the water quality ion concentration interaction parameters, the water quality ion concentration spatial distribution characteristic index analysis unit is used to calculate the water quality ion concentration spatial distribution parameters, and the water quality ion concentration prediction index analysis unit is used to calculate the water quality ion concentration prediction parameters.

[0051] Step 1: By analyzing the dynamic parameters of water quality ion concentration, the stable state of ion concentration in water in time and space can be detected. When the ion concentration in water is in dynamic equilibrium, it means that its concentration fluctuates within a certain range but remains stable overall. A higher dynamic equilibrium index helps to improve the accuracy and reliability of water quality ion concentration detection. Therefore, the model for obtaining the dynamic equilibrium detection index of water quality ion concentration in the water quality ion concentration dynamic equilibrium detection index analysis unit is:

[0052]

[0053] Among them Cdei i It represents the dynamic balance detection index of the ion concentration of the i-th water quality, C 2 Indicates the current ion detection concentration value, C 1Indicates the ion detection concentration value at the previous time point, Max means taking the maximum value, that is, real-time detection of ion concentration at equal time intervals (such as 5 hours, 8 hours, 10 hours), and recording the concentration value, taking the maximum value of ion concentration in adjacent time intervals, which can reflect the dynamic change of ion concentration, C 0 represents the average value of the ion detection concentration within the time interval, v s represents the water flow rate, which affects the distribution of ions. λ represents the ambient temperature adjustment coefficient, which is determined based on experiments and is used to adjust the effect of temperature on the dynamic balance of ions.

[0054] Step 2: By analyzing the interaction parameters of water quality ion concentration, the interaction between different ions can be detected, and the concentration of various ions in water can be accurately determined. By comprehensively considering factors such as the main ion concentration, coexisting ion concentration, pH value and turbidity, the interaction between different ions and its impact on the overall water quality can be more accurately understood. Therefore, the model for obtaining the water quality ion concentration interaction index in the water quality ion concentration interaction index analysis unit is:

[0055]

[0056] Among them Wcii i Represents the interactive index of the ion concentration of the i-th water quality, Ic i Indicates the concentration of the i-th water ion, such as calcium Ca 2+ , magnesium Mg 2+ The content level of (Cic) i represents the concentration of coexisting ions that interact with the i-th water ion, for example, carbonate CO 3 2- and sulfate SO 4 2- The presence of Ca may affect 2+ and magnesium Mg 2+ The solubility of ions forms precipitation or changes its existence form, which in turn affects the detection of ion concentration. PH_b represents the standard deviation of the pH value of the water environment during the water quality detection period, and PH_p represents the average pH value of the water environment. The pH value of the water body affects the precipitation, dissolution and other reactions between ions. NTU_b represents the standard deviation of the turbidity of the water environment during the water quality detection period, and NTU_p represents the average turbidity of the water environment. The turbidity of the water body reflects the content of suspended matter and may affect the detection of ion concentration. The pH value can be measured by a pH meter to measure the pH value of the water body, and the turbidity can be measured by a turbidity meter to measure the turbidity of the water body.

[0057] Step 3: By analyzing the spatial distribution parameters of water quality ion concentration, the spatial distribution differences of ion concentration can be detected. If only some areas are tested, the changes in ion concentration in other areas may be ignored, resulting in incomplete and inaccurate test results. Therefore, when testing water quality ion concentration, it is necessary to fully consider the impact of spatial distribution heterogeneity and formulate scientific sampling plans and analysis methods. Therefore, the model for obtaining the spatial distribution characteristic index of water quality ion concentration in the water quality ion concentration spatial distribution characteristic index analysis unit is:

[0058]

[0059] Among them Sdhi i represents the spatial distribution characteristic index of the ion concentration of the i-th water quality, L represents the number of detection layers of the spatial distribution, Ic i l represents the concentration of the i-th water ion in the l-th layer, Ic i l represents the concentration of the i-th water ion in the l+1 layer, d l+1 represents the depth of the l+1th layer, d l Indicates the depth of the lth layer;

[0060] Step 4: By analyzing the water quality ion concentration prediction parameters, we can understand the problems and challenges that the water body may face in advance through historical detection data. Future trend prediction can improve the foresight and pertinence of water quality ion concentration detection, timely discover potential water quality problems and take corresponding prevention and control measures. Therefore, the model for obtaining water quality ion concentration prediction indicators in the water quality ion concentration prediction indicator analysis unit is:

[0061]

[0062] Icpi i Ic represents the prediction index of the ion concentration of the i-th water quality, p Indicates the average value of ion concentration during water quality ion concentration detection, Ic b Indicates the standard deviation of water ion concentration in the same period of the past three years, Ic M Indicates the ion concentration at the Mth time in the past, Ic 0 Indicates the current ion concentration, M indicates the value in the most recent period, and M is smaller than the value during the water quality ion concentration detection period. For example, M indicates the past 3 days, and the water quality ion concentration detection period is 5 days;

[0063] The water quality ion concentration detection and evaluation module is used to compare the fully automatic water quality ion concentration detection index obtained by the data analysis module with the set value, and output the comparison result to the water quality ion concentration detection comprehensive analysis module. The evaluation module includes the following steps:

[0064] Step 1: The water quality ion concentration dynamic balance detection index analysis calculation result Cdei obtained in the water quality ion concentration dynamic balance detection index analysis unit i Substituting into the formula: Where γ(Cdei i ) represents the rationality factor of the dynamic balance detection index of water quality ion concentration, Cdei 0 Indicates the set value;

[0065] In this embodiment, it should be specifically explained that if γ(Cdei i )≥1, indicating that the dynamic balance of the water ion concentration is good; otherwise, it is considered as γ(Cdei i )=0, and send a warning signal to the water quality ion concentration detection human-computer interaction module.

[0066] Step 2: Obtain the water quality ion concentration interaction index analysis calculation result Wcii from the water quality ion concentration interaction index analysis unit i Substituting into the formula: Where γ(Wcii i ) represents the rationality factor of the interaction index of water quality ion concentration, Wcii 0 Indicates the set value;

[0067] In this embodiment, it should be specifically explained that if γ(Wcii i )≤1, indicating that the detected water ion concentrations interact well, otherwise it is considered as γ(Wcii i )=0, and send a warning signal to the water quality ion concentration detection human-computer interaction module, because strong ion interaction may mask the true concentration of ions, resulting in deviation in the detection results.

[0068] Step 3: Obtain the water quality ion concentration spatial distribution characteristic index analysis calculation result Sdhi from the water quality ion concentration spatial distribution characteristic index analysis unit i Substituting into the formula: Where γ(Sdhi i ) represents the rationality factor of the spatial distribution characteristic index of water quality ion concentration, Sdhi 0 Indicates the set value;

[0069] In this embodiment, it should be specifically explained that if γ(Sdhi i )≥1, indicating that the spatial distribution of the detected water ion concentration is good, otherwise it is considered as γ(Sdhi i )=0, and send a warning signal to the water quality ion concentration detection human-computer interaction module.

[0070] Step 4: Obtain the water quality ion concentration prediction index analysis calculation result Icpi from the water quality ion concentration prediction index analysis unit iSubstituting into the formula: Where γ(Icpi i ) represents the rationality factor of water quality ion concentration prediction index, Icpi 0 Indicates the set value;

[0071] In this embodiment, it should be specifically explained that if γ(Icpi i )≥1, indicating that the predicted water quality ion concentration is accurate, otherwise it is considered as γ(Sdhi i )=0, and send a warning signal to the water quality ion concentration detection human-computer interaction module.

[0072] The water quality ion concentration detection comprehensive analysis module is used to comprehensively analyze the rationality factors calculated by the evaluation module to obtain the comprehensive detection index of water quality ion concentration, and output the comprehensive analysis results to the water quality ion concentration detection human-computer interaction module. Its comprehensive analysis model is:

[0073]

[0074] Where Icci represents the comprehensive detection index of water quality ion concentration, and n represents the number of water quality ion types;

[0075] The water quality ion concentration detection human-computer interaction module is used to output the comprehensive detection index of water quality ion concentration transmitted by the comprehensive analysis module to the detection administrator information terminal. If the comprehensive detection index of water quality ion concentration belongs to the set allowable range, it means that the detected water quality ion concentration content meets the standard. Otherwise, the detection administrator is prompted to take timely measures to identify abnormal values ​​and increase the frequency of water quality detection. On the one hand, a more scientific and reasonable water quality management strategy is formulated, such as optimizing water treatment technology, strengthening pollution source control, and improving water flow conditions; on the other hand, a scientific and reasonable detection plan and analysis method are formulated to ensure the accuracy and reliability of water quality ion concentration detection.

[0076] Secondly: In the drawings of the embodiments disclosed in the present invention, only the structures related to the embodiments disclosed in the present invention are involved, and other structures can refer to the general design. In the absence of conflict, the same embodiment and different embodiments of the present invention can be combined with each other;

[0077] Finally: The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the protection scope of the present invention.

Claims

1. A fully automatic water quality ion concentration detection system based on AI technology, characterized by: It includes water quality ion concentration detection area division module, water quality ion concentration data acquisition module, AI technology data analysis module, water quality ion concentration detection evaluation module, water quality ion concentration detection comprehensive analysis module and water quality ion concentration detection human-computer interaction module; The water quality ion concentration detection area division module is used to take the water quality ions to be detected in the water environment as the target area, and divide it into a number of areas according to each water quality ion, which are sequentially recorded as 1, 2, 3, ..., i, ..., n; The water quality ion concentration data acquisition module is used to collect water quality ion concentration data in the water environment through sensor technology, obtain and analyze various monitoring parameters of the fully automatic water quality ion concentration detection index, and output various monitoring parameters to the AI ​​technology data analysis module; The AI ​​technology data analysis module includes a water quality ion concentration dynamic balance detection index analysis unit, a water quality ion concentration interaction index analysis unit, a water quality ion concentration spatial distribution characteristic index analysis unit, and a water quality ion concentration prediction index analysis unit, and outputs the analysis results of each analysis unit to the water quality ion concentration detection and evaluation module; The water quality ion concentration detection and evaluation module is used to compare the fully automatic water quality ion concentration detection index obtained by the data analysis module with the set value, and output the comparison result to the water quality ion concentration detection comprehensive analysis module; The water quality ion concentration detection comprehensive analysis module is used to comprehensively analyze the rationality factors calculated by the evaluation module, and output the comprehensive analysis results to the water quality ion concentration detection human-computer interaction module; The water quality ion concentration detection human-computer interaction module is used to output the comprehensive detection index of water quality ion concentration transmitted by the comprehensive analysis module to the detection administrator information terminal.

2. According to claim 1, a fully automatic water quality ion concentration detection system based on AI technology is characterized in that: The monitoring parameters in the water quality ion concentration data acquisition module include the detection administrator's identity authentication information, water quality ion concentration dynamic parameters, water quality ion concentration interactive parameters, water quality ion concentration spatial distribution parameters and water quality ion concentration prediction parameters, among which the water quality ion concentration dynamic parameters are specifically the current ion detection concentration value, the ion detection concentration value at the previous time point, the average ion detection concentration and the water quality flow rate; the water quality ion concentration interactive parameters are specifically the concentration of water quality ions, the coexisting ion concentration, the standard deviation of the pH value during the water quality detection, the average pH value, the standard deviation of the water environment turbidity and the average water environment turbidity; the water quality ion concentration spatial distribution parameters are specifically the number of detection layers in the spatial distribution, the water quality ion concentration of each layer and the depth of water quality detection; the water quality ion concentration prediction parameters are specifically the average ion concentration during the water quality ion concentration detection, the water quality ion concentration in the same period of the past three years and the water quality ion concentration detected in the most recent period.

3. According to claim 1, a fully automatic water quality ion concentration detection system based on AI technology is characterized in that: The model for obtaining the water quality ion concentration dynamic balance detection index in the water quality ion concentration dynamic balance detection index analysis unit is: Among them Cdei i represents the dynamic balance detection index of the ion concentration of the i-th water quality, C2 represents the current ion detection concentration value, C1 represents the ion detection concentration value at the previous time point, Max represents the maximum value, C0 represents the average value of the ion detection concentration within the time interval, v s represents the water mass flow rate, and λ represents the ambient temperature adjustment coefficient.

4. According to claim 1, a fully automatic water quality ion concentration detection system based on AI technology is characterized in that: The model for obtaining the water quality ion concentration interaction index in the water quality ion concentration interaction index analysis unit is: Among them Wcii i Represents the interactive index of the ion concentration of the i-th water quality, Ic i Represents the concentration of the i-th water ion, (Cic) i It represents the concentration of coexisting ions that interact with the i-th water quality ion, PH_b represents the standard deviation of the pH value of the water environment during the water quality detection period, PH_p represents the average pH value of the water environment, NTU_b represents the standard deviation of the turbidity of the water environment during the water quality detection period, and NTU_p represents the average turbidity of the water environment.

5. According to claim 1, a fully automatic water quality ion concentration detection system based on AI technology is characterized in that: The model for obtaining the water quality ion concentration spatial distribution characteristic index in the water quality ion concentration spatial distribution characteristic index analysis unit is: Among them Sdhi i represents the spatial distribution characteristic index of the ion concentration of the i-th water quality, L represents the number of detection layers of the spatial distribution, Ic i l represents the concentration of the i-th water ion in the l-th layer, Ic i l represents the concentration of the i-th water ion in the l+1 layer, d l+1 represents the depth of the l+1th layer, d l Indicates the depth of layer l.

6. The fully automatic water quality ion concentration detection system based on AI technology according to claim 1 is characterized in that: The model for obtaining the water quality ion concentration prediction index in the water quality ion concentration prediction index analysis unit is: Icpi i Ic represents the prediction index of the ion concentration of the i-th water quality, p Indicates the average value of ion concentration during water quality ion concentration detection, Ic b Indicates the standard deviation of water ion concentration in the same period of the past three years, Ic M It represents the ion concentration at the Mth time in the past, Ic0 represents the current ion concentration, M represents the value in the most recent period, and M is smaller than the value during the water quality ion concentration detection period.

7. The fully automatic water quality ion concentration detection system based on AI technology according to claim 1 is characterized by: The water quality ion concentration detection and evaluation module includes the following steps: Step 1: The water quality ion concentration dynamic balance detection index analysis calculation result Cdei obtained in the water quality ion concentration dynamic balance detection index analysis unit i Substituting into the formula: Where γ(Cdei i ) represents the rationality factor of the dynamic balance detection index of water quality ion concentration, and Cdei0 represents the set value; Step 2: Obtain the water quality ion concentration interaction index analysis calculation result Wcii from the water quality ion concentration interaction index analysis unit i Substituting into the formula: Where γ(Wcii i ) represents the rationality factor of the water quality ion concentration interaction index, and Wcii0 represents the set value; Step 3: Obtain the water quality ion concentration spatial distribution characteristic index analysis calculation result Sdhi from the water quality ion concentration spatial distribution characteristic index analysis unit i Substituting into the formula: Where γ(Sdhi i ) represents the rationality factor of the water quality ion concentration spatial distribution characteristic index, and Sdhi0 represents the set value; Step 4: Obtain the water quality ion concentration prediction index analysis calculation result Icpi from the water quality ion concentration prediction index analysis unit i Substituting into the formula: Where γ(Icpi i ) represents the rationality factor of the water quality ion concentration prediction index, and Icpi0 represents the set value.

8. The fully automatic water quality ion concentration detection system based on AI technology according to claim 1 is characterized by: The comprehensive analysis model in the water quality ion concentration detection comprehensive analysis module is: Among them, Icci represents the comprehensive detection index of water quality ion concentration, and n represents the number of water quality ion types.

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