An online water quality monitoring system and method for environmental monitoring

Abstract

The invention discloses an online monitoring system and method for water quality for environmental monitoring, and relates to the technical field of online monitoring of water quality. A data acquisition module is responsible for real-time acquisition of online monitoring data related to dissolved oxygen, chemical oxygen demand and total phosphorus of water quality, a data transmission module is responsible for real-time transmission of the collected online monitoring data to a remote data center, a data processing module is responsible for receiving and storing the online monitoring data from the data acquisition module, and an early warning and response module is responsible for triggering early warning information according to the water quality change trend displayed in a line graph and the set early warning conditions. The invention monitors three water quality parameters in real time, and integrates the three water quality parameters to achieve the purpose of comprehensive evaluation and monitoring, and has powerful data processing capabilities and stable data transmission, which not only improves the accuracy and efficiency of water quality monitoring, but also provides a scientific basis and intelligent early warning function for water quality management and protection.

Description

Technical Field

[0001] The present invention relates to the technical field of water quality online monitoring, and in particular to an online water quality monitoring system and method for environmental monitoring. Background Art

[0002] In the field of environmental monitoring, water quality monitoring is an important means to assess the health of water bodies, protect water resources and ensure water quality safety. Its monitoring work is of great significance to ensuring the safety of water resources and promoting the sustainable use of water resources. Water quality monitoring helps to detect water quality problems in a timely manner and provide a scientific basis for the protection and rational use of water resources. Among them, water quality deterioration poses a serious threat to human health and the ecological environment. Through water quality monitoring, potential water pollution problems can be discovered and warned in a timely manner, so that corresponding measures can be taken to prevent the spread of pollution and protect human health and the ecological environment.

[0003] At present, the existing online water quality monitoring systems can often only monitor one or several water quality parameters separately, and thus cannot fully reflect the water quality status of the water body. Although some systems can monitor multiple water quality parameters, their data processing capabilities are limited and they cannot conduct in-depth analysis and processing of the monitoring data, thus failing to obtain accurate water quality evaluation results. Among them, data transmission is one of the key links in the online water quality monitoring system, but the existing systems often have the problem of unstable data transmission, resulting in the inability to transmit the monitoring data to the background system for processing and analysis in a timely manner. In addition, most of the existing systems lack a comprehensive water quality evaluation index, thus failing to conduct a comprehensive and objective evaluation of the water quality. Summary of the invention

[0004] The purpose of the present invention is to provide an online water quality monitoring system for environmental monitoring, which solves the problems raised in the above-mentioned background technology.

[0005] To achieve the above object, the present invention provides the following technical solution, including online monitoring of dissolved oxygen, chemical oxygen demand and total phosphorus;

[0006] It includes data acquisition module, data transmission module, data processing module, display and analysis module, early warning and response module, and its specific implementation is as follows:

[0007] Data acquisition module: responsible for real-time collection of online monitoring data related to dissolved oxygen, chemical oxygen demand and total phosphorus of water quality, and converting them into digital signals;

[0008] Data transmission module: responsible for transmitting the collected online monitoring data to the remote data center in real time;

[0009] Data processing module: responsible for receiving and storing the online monitoring data from the data acquisition module, and calculating and outputting the dissolved oxygen concentration RY, the estimated value of chemical oxygen demand HY, and the comprehensive water quality index SZ in turn;

[0010] Display and analysis module: responsible for drawing the estimated chemical oxygen demand HY at N moments into a line graph, showing the trend of water quality changes, and conducting trend analysis;

[0011] Early warning and response module: responsible for triggering early warning information and taking corresponding emergency response measures according to the water quality change trend shown in the line chart and the set early warning conditions;

[0012] The data processing module includes a unit for real-time monitoring and rapid response of water quality changes, a unit for measuring the content of organic pollutants in the water body, and a unit for comprehensively reflecting the water quality status.

[0013] Optionally, the equipment used by the data acquisition module includes a dissolved oxygen sensor, a chemical oxygen demand sensor, a total phosphorus sensor, and a data acquisition device;

[0014] The equipment used by the data transmission module includes wireless communication equipment;

[0015] The equipment used by the data processing module includes a remote data center server;

[0016] The equipment used by the display and analysis module includes a display device;

[0017] The equipment used by the early warning and response module includes an alarm device.

[0018] Optionally, the calculation formula of the water quality change real-time monitoring and rapid response unit is as follows:

[0019] RY=[YC×(YD+YG)-P1] / (L1×SQRT(W));

[0020] L1=(YC-YC0) / (RY true -RY0);

[0021] in:

[0022] RY is the dissolved oxygen concentration;

[0023] YC is the output value of the oxygen sensor. YC represents the output value of voltage / current according to the sensor type;

[0024] YD is the low range calibration value of the oxygen sensor;

[0025] YG is the high range calibration value of the oxygen sensor;

[0026] P1 is the first offset, which reflects the offset degree of the zero point of the oxygen sensor;

[0027] L1 is the first sensitivity coefficient and reflects the sensitivity of the oxygen sensor;

[0028] YC0 is the average output value of the oxygen sensor;

[0029] RY true is the actual dissolved oxygen concentration, RY true Refers to the actual content of dissolved oxygen in water, and is directly measured through chemical analysis, including iodine titration and membrane electrode method, to reflect the actual situation of dissolved oxygen in water;

[0030] RY0 is the average concentration of dissolved oxygen;

[0031] W is the current water temperature.

[0032] Optionally, the calculation formula for measuring the unit of organic pollutant content in water is as follows:

[0033] HY={RY lasttime ×(HC / HC max )-[RY×(1-(HC / HC max ))]}+[(RY lasttime -RY)×

[0034] (TJ / SQRT(LL))];

[0035] in:

[0036] HY is the estimated value of chemical oxygen demand;

[0037] RY lasttime is the dissolved oxygen concentration at the previous moment;

[0038] HC is the output value of the chemical oxygen demand sensor. HC represents the output value of voltage / current according to the sensor type;

[0039] HC max is the maximum output value of the chemical oxygen demand sensor;

[0040] TJ is the specific calibration factor;

[0041] LL is the flow parameter, and LL is the reading of the flow meter.

[0042] Optionally, the calculation formula of the specific calibration coefficient TJ is as follows:

[0043] TJ=f(HC,HC true );

[0044] f(HC,HC true ) is a linear relationship model, and the linear equation is specifically expanded as follows:

[0045] y=mx+b;

[0046] y is the dependent variable, i.e., HC;

[0047] m is the slope;

[0048] x is the independent variable, that is, HC true ;

[0049] b is the intercept;

[0050] During the calibration process, a set of solutions with known chemical oxygen demand (x1, x2, ..., xn) and the corresponding sensor output values ​​(y1, y2, ..., yn) are substituted into the linear equation and the values ​​of m and b are solved;

[0051] Since m is the slope and describes the slope of the linear relationship between the independent variable x and the dependent variable y, and the size and direction of the slope m determines how the dependent variable y will change as the independent variable x changes, TJ = m.

[0052] Optionally, the calculation formula for the unit that comprehensively reflects the water quality status is as follows:

[0053] SZ=SQRT[(HY-HY0)×(RY / RY0)+(ZL×(TPC / TPC max ))] / SL;

[0054] in:

[0055] SZ is the comprehensive water quality index;

[0056] HY0 is the estimated average value of chemical oxygen demand;

[0057] ZL is the total phosphorus concentration;

[0058] TPC is the output value of the total phosphorus sensor. TPC represents the output value of voltage / current according to the sensor type;

[0059] TPC max is the maximum output value of the total phosphorus sensor;

[0060] SL is the number of parameters, and SL reflects the sum of the parameters introduced into the calculation of the unit that comprehensively reflects the water quality status.

[0061] Optionally, the calculation formula of the total phosphorus concentration ZL is as follows:

[0062] ZL=[TPC×(TPD+TPG)-P2] / (L2×SQRT(W));

[0063] L2=(TPC-TPC0) / (ZL true -ZL0);

[0064] TPD is the low range calibration value of the total phosphorus sensor;

[0065] TPG is the high range calibration value of the total phosphorus sensor;

[0066] P2 is the second offset, which reflects the offset degree of the zero point of the total phosphorus sensor;

[0067] L2 is the second sensitivity coefficient and reflects the sensitivity of the total phosphorus sensor;

[0068] TPC0 is the average output value of the total phosphorus sensor;

[0069] ZL true is the actual total phosphorus concentration;

[0070] ZL0 is the average concentration of total phosphorus.

[0071] Optionally, the online monitoring analysis based on the comprehensive water quality index SZ is as follows:

[0072] If the water quality comprehensive index SZ shows an upward trend on the line graph, it means that the water quality is deteriorating, the system will receive an early warning message and immediately initiate the emergency response procedure;

[0073] If the water quality comprehensive index SZ shows a downward trend on the line graph, it means that the water quality is improving and the system will maintain the current monitoring;

[0074] If the comprehensive water quality index SZ shows a flat trend on the line graph, it means that the water quality is relatively stable and the system will increase the monitoring frequency.

[0075] The object of the present invention is to provide an online monitoring method for water quality for environmental monitoring, including an online monitoring method for dissolved oxygen, chemical oxygen demand and total phosphorus;

[0076] It includes data collection module, data transmission module, data processing module, display and analysis module, and early warning and response module;

[0077] The specific steps are as follows:

[0078] Step 1: using the data acquisition module to collect online monitoring data related to dissolved oxygen, chemical oxygen demand and total phosphorus of water quality in real time, and converting them into digital signals;

[0079] Step 2: using the data transmission module to transmit the collected online monitoring data to the remote data center of the data processing module in real time;

[0080] Step 3: using the data processing module, sequentially calculate and output the dissolved oxygen concentration RY, the estimated value of chemical oxygen demand HY, and the comprehensive water quality index SZ;

[0081] Step 4: Based on the comprehensive water quality index SZ, the water quality change trend and trend analysis are displayed using the display and analysis module;

[0082] Step 5: Use the early warning and response module to provide timely early warning and measure control for changing trends.

[0083] Compared with the prior art, the present invention has the following beneficial effects:

[0084] 1. The system of the present invention monitors three water quality parameters of dissolved oxygen, chemical oxygen demand and total phosphorus in real time, thereby comprehensively reflecting the water quality status of the water body, and by introducing a unit for real-time monitoring and rapid response to water quality changes, a unit for measuring the content of organic pollutants in the water body, and a unit for comprehensively reflecting the water quality status, the system can conduct in-depth analysis and processing of the monitoring data, thereby obtaining accurate water quality evaluation results. In addition, the parameter values ​​in the unit for real-time monitoring and rapid response to water quality changes, the unit for measuring the content of organic pollutants in the water body, and the unit for comprehensively reflecting the water quality status need to be obtained through experimental calibration, thereby ensuring the accuracy and reliability of the data.

[0085] 2. The present invention adopts advanced wireless communication technology to realize real-time remote transmission of monitoring data and ensure the stability and reliability of data transmission.

[0086] 3. The present invention calculates the comprehensive water quality index SZ by comprehensively reflecting the water quality status units, and conducts a comprehensive and objective evaluation of the water quality. At the same time, the system also introduces a line graph to observe the changing trend of the comprehensive water quality index SZ, and changes the monitoring frequency and issues early warnings based on the trend, thereby improving the flexibility and accuracy of water quality monitoring. BRIEF DESCRIPTION OF THE DRAWINGS

[0087] Figure 1 This is a flow chart of the method for online monitoring of water quality used in this environmental monitoring;

[0088] Figure 2 It is a structural schematic diagram of the data processing module of the present invention;

[0089] Figure 3 It is a schematic diagram of the rising trend of the comprehensive water quality index SZ in the linear graph of the present invention;

[0090] Figure 4 It is a schematic diagram of the downward trend of the comprehensive water quality index SZ in the linear graph of the present invention;

[0091] Figure 5 It is a schematic diagram of the gentle trend of the comprehensive water quality index SZ on the linear graph in the present invention. DETAILED DESCRIPTION

[0092] 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.

[0093] The present online water quality monitoring system and method for environmental monitoring is different from the existing online water quality monitoring systems and methods for environmental monitoring. Most of the existing online water quality monitoring systems and methods for environmental monitoring have some problems, including single monitoring parameters, limited data processing capabilities, and unstable data transmission. In addition, the existing systems often lack a comprehensive water quality evaluation index and cannot fully reflect the overall water quality status of the water body. The present algorithm unit monitors three water quality parameters in real time and integrates the three water quality parameters to achieve the purpose of comprehensive evaluation and monitoring. It also has powerful data processing capabilities and stable data transmission, which not only improves the accuracy and efficiency of water quality monitoring, but also provides a scientific basis and intelligent early warning function for water quality management and protection.

[0094] For example, see Figures 1 to 5 ,This implementation provides an online monitoring system for water quality for environmental monitoring, including online monitoring of dissolved oxygen, chemical oxygen demand and total phosphorus;

[0095] It includes data acquisition module, data transmission module, data processing module, display and analysis module, and early warning and response module.

[0096] This embodiment also provides an online monitoring method for water quality for environmental monitoring, including an online monitoring method for dissolved oxygen, chemical oxygen demand and total phosphorus;

[0097] It includes data collection module, data transmission module, data processing module, display and analysis module, and early warning and response module;

[0098] The specific steps are as follows:

[0099] Step 1: Use the data acquisition module to collect online monitoring data related to dissolved oxygen, chemical oxygen demand and total phosphorus of water quality in real time and convert them into digital signals;

[0100] Step 2: Use the data transmission module to transmit the collected online monitoring data to the remote data center of the data processing module in real time;

[0101] Step 3: Using the data processing module, calculate and output the dissolved oxygen concentration RY, the estimated value of chemical oxygen demand HY, and the comprehensive water quality index SZ in sequence;

[0102] Step 4: Based on the comprehensive water quality index SZ, use the display and analysis module to display the water quality change trend and trend analysis;

[0103] Step 5: Use the early warning and response module to provide timely early warning and control measures for changing trends.

[0104] In this embodiment, the system cooperates with the three algorithm units and combines the three operation results of RY, HY and SZ to form an accurate measurement and comprehensive analysis system for water quality parameters. Specifically, RY is the dissolved oxygen concentration, which is an important parameter in water quality monitoring. It is directly related to the biological activity, redox state and pollution degree of the water body. Through RY, combined with the output value of the oxygen sensor and a series of calibration parameters, the dissolved oxygen concentration RY can be calculated in real time. This calculation process not only improves the measurement accuracy, but also realizes a rapid response to water quality changes. HY is the chemical requirement. The estimated value of oxygen content reflects the degree of organic pollution in the water body and provides a basis for evaluating the degree of organic pollution in the water body. SZ is the comprehensive water quality index, which is a dimensionless indicator that comprehensively reflects the water quality status. This calculation process not only realizes the comprehensive evaluation of water quality parameters, but also provides a scientific basis for water quality management. The calculation result of SZ can also affect the calculation of RY and HY, so that the three algorithms of this system have different calculation purposes in the online water quality monitoring system, which not only improves the accuracy and efficiency of water quality monitoring, but also provides a scientific basis and intelligent early warning function for water quality management and protection.

[0105] See also Figures 1 to 5 , the calculation formula of the water quality change real-time monitoring and rapid response unit is as follows:

[0106] RY=[YC×(YD+YG)-P1] / (L1×SQRT(W));

[0107] L1=(YC-YC0) / (RY true -RY0);

[0108] in:

[0109] RY is the dissolved oxygen concentration;

[0110] YC is the output value of the oxygen sensor. YC represents the output value of voltage / current according to the sensor type;

[0111] YD is the low range calibration value of the oxygen sensor;

[0112] YG is the high range calibration value of the oxygen sensor;

[0113] P1 is the first offset, which reflects the offset degree of the zero point of the oxygen sensor;

[0114] L1 is the first sensitivity coefficient and reflects the sensitivity of the oxygen sensor;

[0115] YC0 is the average output value of the oxygen sensor;

[0116] RY true is the actual dissolved oxygen concentration, RY true Refers to the actual content of dissolved oxygen in water, and is directly measured through chemical analysis, including iodine titration and membrane electrode method, to reflect the actual situation of dissolved oxygen in water;

[0117] RY0 is the average concentration of dissolved oxygen;

[0118] W is the current water temperature.

[0119] In this embodiment: First, the calculation part "(YD+YG)-P1" in this algorithm unit is to linearize the output of the oxygen sensor and correct the zero offset, wherein YD is the low-range calibration value of the oxygen sensor, and YG is the high-range calibration value of the oxygen sensor. These two parameters together define the linear response range of the sensor, and P1 is the first offset, which is used to correct the output of the sensor when there is no dissolved oxygen. This calculation part can obtain a more accurate sensor output value through linearization and zero point correction, and then calculate a more accurate dissolved oxygen concentration RY;

[0120] The calculation part of "(L1×SQRT(W))" takes into account the effect of temperature on dissolved oxygen concentration RY. L1 is the first sensitivity coefficient, and "SQRT(W)" is the square root operation of temperature, which reflects the nonlinear effect of temperature on dissolved oxygen solubility. This calculation part can make the calculated dissolved oxygen concentration RY closer to the actual value by adjusting the temperature effect, that is, closer to the actual dissolved oxygen concentration RY. true , especially under different water temperature conditions;

[0121] This algorithm unit can significantly improve the measurement accuracy of dissolved oxygen concentration by accurately calibrating the sensor and taking into account the influence of low-range and high-range parameters. This high-precision measurement is of great significance for evaluating the biological activity, redox state and pollution degree of water bodies. Since the sensor can collect data in real time, the real-time monitoring and rapid response unit of water quality changes can instantly calculate the dissolved oxygen concentration, thereby achieving a rapid response to water quality changes, which is crucial for timely detection of water quality problems, prevention of pollution incidents and formulation of emergency measures.

[0122] The parameters in the water quality change real-time monitoring and rapid response unit are adjusted according to the actual water quality and sensor characteristics to meet the monitoring needs in different environments. This flexibility enables the water quality change real-time monitoring and rapid response unit to be widely used in various types of water body monitoring;

[0123] Among them, the low-range calibration value YD of the oxygen sensor refers to the lowest concentration value that the oxygen sensor can accurately detect within the measuring range. This value is usually determined through the calibration process when the sensor leaves the factory and before use, and is used to ensure the accuracy of the data when measuring low concentrations of dissolved oxygen. In contrast to the low range, the high-range calibration value YG of the oxygen sensor refers to the highest concentration value that the oxygen sensor can accurately detect. This value is also determined through the calibration process, and is used to ensure the accuracy of the data at high concentrations of dissolved oxygen. The calibration values ​​of the low and high ranges are usually measured by exposing the sensor to dissolved oxygen solutions of known concentrations. These solutions of known concentrations can be prepared by standard methods, including the use of saturated salt solutions and specific chemical reagents. During the calibration process, the output values ​​of the sensor at these known concentrations are recorded and compared with the actual concentrations to determine the calibration values ​​of the low and high ranges.

[0124] See also Figures 1 to 5 , the calculation formula for measuring the unit of organic pollutant content in water is as follows:

[0125] HY={RY lasttime ×(HC / HC max )-[RY×(1-(HC / HC max ))]}+[(RY lasttime -RY)×

[0126] (TJ / SQRT(LL))];

[0127] in:

[0128] HY is the estimated value of chemical oxygen demand;

[0129] RY lasttime is the dissolved oxygen concentration at the previous moment;

[0130] HC is the output value of the chemical oxygen demand sensor. HC represents the output value of voltage / current according to the sensor type;

[0131] HC max is the maximum output value of the chemical oxygen demand sensor;

[0132] TJ is the specific calibration factor;

[0133] LL is the flow parameter, and LL is the reading of the flow meter;

[0134] The specific calibration factor TJ is calculated as follows:

[0135] TJ=f(HC,HC true );

[0136] f(HC,HC true) is a linear relationship model, and the linear equation is specifically expanded as follows:

[0137] y=mx+b;

[0138] y is the dependent variable, i.e., HC;

[0139] m is the slope;

[0140] x is the independent variable, that is, HC true ;

[0141] b is the intercept;

[0142] During the calibration process, a set of solutions with known chemical oxygen demand (x1, x2, ..., xn) and the corresponding sensor output values ​​(y1, y2, ..., yn) are substituted into the linear equation and the values ​​of m and b are solved;

[0143] Since m is the slope and describes the slope of the linear relationship between the independent variable x and the dependent variable y, and the size and direction of the slope m determines how the dependent variable y will change as the independent variable x changes, TJ = m.

[0144] In this embodiment, first, "RY lasttime ×(HC / HC max )” calculation part is to use the dissolved oxygen concentration RY at the previous moment lasttime and the relative output value of the chemical oxygen demand sensor "(HC / HC max )” to estimate the change of chemical oxygen demand, which reflects the trend of dissolved oxygen concentration RY changing with chemical oxygen demand, and by considering the change of dissolved oxygen concentration RY, the value of chemical oxygen demand can be estimated more accurately, because the consumption of chemical oxygen demand will lead to the decrease of dissolved oxygen concentration RY, “RY×(1-(HC / HC max The calculation part takes into account the current hand-held dissolved oxygen concentration RY and the relative output value of the chemical oxygen demand sensor to estimate the remaining dissolved oxygen concentration under the current chemical oxygen demand level. It reflects the consumption of dissolved oxygen by the current chemical oxygen demand level, and by calculating the remaining dissolved oxygen concentration, the estimated value of chemical oxygen demand can be further corrected to make it more accurate;

[0145] This algorithm combines the output of dissolved oxygen concentration RY and chemical oxygen demand sensors to enable the unit that measures the content of organic pollutants in water to more comprehensively assess the degree of organic pollution in water. This comprehensive assessment helps to discover potential pollution sources and pollution trends, and provides a basis for formulating effective water quality management strategies.

[0146] The unit for measuring the content of organic pollutants in water bodies can capture the dynamic process of water quality changes, especially the changes in dissolved oxygen concentration RY. This dynamic monitoring capability helps to detect water quality abnormalities in a timely manner and prevent pollution incidents;

[0147] The algorithm can also optimize the estimation process of chemical oxygen demand and improve the monitoring efficiency by adjusting the flow parameter LL and the specific calibration coefficient TJ of the chemical oxygen demand sensor. This optimization helps to reduce the monitoring cost and improve the accuracy and reliability of the monitoring data.

[0148] See also Figures 1 to 5 , the calculation formula for the unit that comprehensively reflects the water quality status is as follows:

[0149] SZ=SQRT[(HY-HY0)×(RY / RY0)+(ZL×(TPC / TPC max ))] / SL;

[0150] in:

[0151] SZ is the comprehensive water quality index;

[0152] HY0 is the estimated average value of chemical oxygen demand;

[0153] ZL is the total phosphorus concentration;

[0154] TPC is the output value of the total phosphorus sensor. TPC represents the output value of voltage / current according to the sensor type;

[0155] TPC max is the maximum output value of the total phosphorus sensor;

[0156] SL is the number of parameters, and SL reflects the sum of the parameters introduced into the calculation of the comprehensive water quality status unit;

[0157] The calculation formula of total phosphorus concentration ZL is as follows:

[0158] ZL=[TPC×(TPD+TPG)-P2] / (L2×SQRT(W));

[0159] L2=(TPC-TPC0) / (ZL true -ZL0);

[0160] TPD is the low range calibration value of the total phosphorus sensor;

[0161] TPG is the high range calibration value of the total phosphorus sensor;

[0162] P2 is the second offset, which reflects the offset degree of the zero point of the total phosphorus sensor;

[0163] L2 is the second sensitivity coefficient and reflects the sensitivity of the total phosphorus sensor;

[0164] TPC0 is the average output value of the total phosphorus sensor;

[0165] ZL true is the actual total phosphorus concentration;

[0166] ZL0 is the average concentration of total phosphorus.

[0167] In this embodiment, the algorithm unit first calculates the difference between the estimated chemical oxygen demand HY and the estimated chemical oxygen demand average HY0 based on the "HY-HY0" calculation part, which reflects the degree of excess of chemical oxygen demand. By considering the degree of excess of chemical oxygen demand, the calculation part can evaluate the content of organic pollutants in water quality and calculate the comprehensive water quality index SZ accordingly;

[0168] The calculation part of "RY / RY0" is the ratio between the adjusted dissolved oxygen concentration RY and the average dissolved oxygen concentration RY0, which reflects the sufficiency of dissolved oxygen. The calculation part can evaluate the self-purification capacity of the water body and the biological respiration demand by considering the sufficiency of dissolved oxygen, and calculate the comprehensive water quality index SZ accordingly;

[0169] “ZL×(TPC / TPC max )” calculation part is to use the output value of the total phosphorus sensor to estimate the total phosphorus concentration ZL, and consider its relative output value “(TPC / TPC max )” to reflect the degree of total phosphorus pollution. This calculation part can evaluate the content of nutrients in water quality by considering the concentration of total phosphorus, and calculate the comprehensive water quality index SZ accordingly. Among them, total phosphorus is one of the important nutrients for algae growth. Too high a content will lead to eutrophication of water bodies.

[0170] This algorithm unit comprehensively considers the three water quality parameters, so that the comprehensive reflection of water quality status unit can comprehensively and objectively evaluate the overall water quality status of the water body. This comprehensive evaluation helps to find the root cause of water quality problems and provide a basis for formulating targeted water quality improvement measures;

[0171] In this embodiment, by introducing a line graph to observe the change trend of the comprehensive water quality index SZ, it is helpful to discover the law of water quality change and potential problems. This trend analysis capability helps to predict the future development trend of water quality and provide a scientific basis for water quality management.

[0172] In this embodiment, the system can automatically trigger warning information according to the change trend of the comprehensive water quality index SZ and the set warning conditions. This intelligent warning function helps to timely discover the deterioration of water quality and take timely measures to prevent further deterioration of water quality.

[0173] In summary, the real-time monitoring and rapid response unit for water quality changes, the unit for measuring the content of organic pollutants in water bodies, and the unit for comprehensively reflecting water quality conditions in the online water quality monitoring system and method for environmental monitoring each have unique beneficial effects. The application of these calculation formulas not only improves the accuracy and efficiency of water quality monitoring, but also provides a scientific basis and intelligent early warning function for water quality management and protection. By comprehensively applying these formulas, we can better understand the water quality status of water bodies, discover and solve water quality problems in a timely manner, and contribute to the sustainable utilization and protection of water resources.

[0174] For example 2, please refer to Figures 1 to 5 , the online monitoring analysis based on the comprehensive water quality index SZ is as follows:

[0175] If the water quality comprehensive index SZ shows an upward trend on the line graph, it means that the water quality is deteriorating, the system will receive an early warning message and immediately initiate the emergency response procedure;

[0176] If the water quality comprehensive index SZ shows a downward trend on the line graph, it means that the water quality is improving and the system will maintain the current monitoring;

[0177] If the comprehensive water quality index SZ shows a flat trend on the line graph, it means that the water quality is relatively stable and the system will increase the monitoring frequency.

[0178] In this embodiment, according to the changing trend of the comprehensive water quality index SZ, the system can dynamically adjust the monitoring frequency. Specifically, when the water quality deteriorates, the monitoring frequency is increased to obtain more detailed data, and when the water quality is stable, the monitoring frequency is reduced to save resources. This adjustment can ensure the timeliness and accuracy of the data, while reducing the monitoring cost. Through long-term observation and analysis of the comprehensive water quality index SZ, the changing trend and error range of the sensor calibration parameters can be found, which helps to regularly calibrate the sensor and update the calibration parameters, and improve the accuracy and reliability of the monitoring data. Then, according to the calculation results of the comprehensive water quality index SZ and the feedback of the monitoring data, the entire monitoring system can be optimized and upgraded, including introducing more advanced sensor technology, optimizing data processing algorithms, and improving data transmission stability, so as to further improve the performance and accuracy of the system.

[0179] Among them, it is worth mentioning that the line graph can intuitively display the trend of the comprehensive water quality index SZ over time by connecting a series of data points. This intuitive display method can quickly capture the changes in water quality without in-depth interpretation of complex data tables and reports. At the same time, the dynamic nature of the line graph can also achieve real-time tracking of water quality conditions, timely adjustment of monitoring strategies and response measures, and the rise, fall and flatness of the line graph trend directly reflect the changes in water quality. Specifically, when the comprehensive water quality index SZ value continues to rise, it means that the water quality is deteriorating. At this time, emergency measures need to be taken to prevent the situation from further deteriorating. On the contrary, when the comprehensive water quality index SZ value continues to decline, it means that the water quality is improving and the current governance plan can continue to be implemented. When the comprehensive water quality index SZ value remains flat, it is necessary to remain vigilant and increase the monitoring frequency, and continue to pay attention to the water quality status to prevent potential risks. This decision-making method based on the trend of the line graph is more scientific and reasonable, which helps to improve the efficiency and effectiveness of water quality management.

[0180] In summary, the real-time monitoring and rapid response unit for water quality changes, the unit for measuring the content of organic pollutants in water bodies, and the unit for comprehensively reflecting water quality conditions play a vital role in the online water quality monitoring system for environmental monitoring. They not only improve the accuracy and efficiency of water quality monitoring, but also provide a scientific basis and intelligent early warning function for water quality management and protection. At the same time, the cyclical impact of the unit for comprehensively reflecting water quality conditions on the real-time monitoring and rapid response unit for water quality changes also promotes the continuous optimization and upgrading of the monitoring system. The introduction of a line graph as a tool for observing the comprehensive water quality index SZ and its relationship with the monitoring frequency and early warning has the effect of providing an intuitive dynamic perspective and assisting decision-making. These effects work together in the field of water quality management, which helps to improve the scientificity and efficiency of water quality management and ensure the safety and stability of water quality.

[0181] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations can be made to the embodiments without departing from the principles and spirit of the present invention, and the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. An online water quality monitoring system for environmental monitoring, characterized in that: Includes online monitoring of dissolved oxygen, chemical oxygen demand and total phosphorus; It also includes data acquisition module, data transmission module, data processing module, display and analysis module, and early warning and response module: Data acquisition module: responsible for real-time collection of online monitoring data related to dissolved oxygen, chemical oxygen demand and total phosphorus of water quality, and converting them into digital signals; Data transmission module: responsible for transmitting the collected online monitoring data to the remote data center in real time; Data processing module: responsible for receiving and storing the online monitoring data from the data acquisition module, and calculating and outputting the dissolved oxygen concentration RY, the estimated value of chemical oxygen demand HY, and the comprehensive water quality index SZ in turn; Display and analysis module: responsible for drawing the estimated chemical oxygen demand HY at N moments into a line graph, showing the trend of water quality changes, and conducting trend analysis; Early warning and response module: responsible for triggering early warning information and taking corresponding emergency response measures according to the water quality change trend shown in the line chart and the set early warning conditions; The data processing module includes a unit for real-time monitoring and rapid response of water quality changes, a unit for measuring the content of organic pollutants in the water body, and a unit for comprehensively reflecting the water quality status.

2. The online water quality monitoring system for environmental monitoring according to claim 1 is characterized in that: The equipment used in the data acquisition module includes a dissolved oxygen sensor, a chemical oxygen demand sensor, a total phosphorus sensor, and a data acquisition device; The equipment used by the data transmission module includes wireless communication equipment; The equipment used by the data processing module includes a remote data center server; The equipment used by the display and analysis module includes a display device; The equipment used by the early warning and response module includes an alarm device.

3. The online water quality monitoring system for environmental monitoring according to claim 2 is characterized in that: The calculation formula of the water quality change real-time monitoring and rapid response unit is as follows: RY=[YC×(YD+YG)-P1] / (L1×SQRT(W)); L1=(YC-YC0) / (RY true -RY0); in: RY is the dissolved oxygen concentration; YC is the output value of the oxygen sensor. YC represents the output value of voltage / current according to the sensor type; YD is the low range calibration value of the oxygen sensor; YG is the high range calibration value of the oxygen sensor; P1 is the first offset, which reflects the offset degree of the zero point of the oxygen sensor; L1 is the first sensitivity coefficient and reflects the sensitivity of the oxygen sensor; YC0 is the average output value of the oxygen sensor; RY true is the actual dissolved oxygen concentration, RY true Refers to the actual content of dissolved oxygen in water, and is directly measured through chemical analysis, including iodine titration and membrane electrode method, to reflect the actual situation of dissolved oxygen in water; RY0 is the average concentration of dissolved oxygen; W is the current water temperature.

4. The online water quality monitoring system for environmental monitoring according to claim 3 is characterized in that: The calculation formula for measuring the unit of organic pollutant content in water is as follows: HY={RY lasttime ×(HC / HC max )-[RY×(1-(HC / HC max ))]}+[(RY lasttime -RY)× (TJ / SQRT(LL))]; in: HY is the estimated value of chemical oxygen demand; RY lasttime is the dissolved oxygen concentration at the previous moment; HC is the output value of the chemical oxygen demand sensor. HC represents the output value of voltage / current according to the sensor type; HC max is the maximum output value of the chemical oxygen demand sensor; TJ is the specific calibration factor; LL is the flow parameter, and LL is the reading of the flow meter.

5. The online water quality monitoring system for environmental monitoring according to claim 4 is characterized in that: The calculation formula of the specific calibration coefficient TJ is as follows: TJ=f(HC,HC true ); f(HC,HC true ) is a linear relationship model, and the linear equation is specifically expanded as follows: y=mx+b; y is the dependent variable, i.e., HC; m is the slope; x is the independent variable, that is, HC true ; b is the intercept; During the calibration process, a set of solutions with known chemical oxygen demand (x1, x2, ..., xn) and the corresponding sensor output values ​​(y1, y2, ..., yn) are substituted into the linear equation and the values ​​of m and b are solved; Since m is the slope and describes the slope of the linear relationship between the independent variable x and the dependent variable y, and the size and direction of the slope m determines how the dependent variable y will change as the independent variable x changes, TJ = m.

6. The online water quality monitoring system for environmental monitoring according to claim 5 is characterized by: The calculation formula for the comprehensive water quality status unit is as follows: SZ=SQRT[(HY-HY0)×(RY / RY0)+(ZL×(TPC / TPC max ))] / SL; in: SZ is the comprehensive water quality index; HY0 is the estimated average value of chemical oxygen demand; ZL is the total phosphorus concentration; TPC is the output value of the total phosphorus sensor. TPC represents the output value of voltage / current according to the sensor type; TPC max is the maximum output value of the total phosphorus sensor; SL is the number of parameters, and SL reflects the sum of the parameters introduced into the calculation of the unit that comprehensively reflects the water quality status.

7. The online water quality monitoring system for environmental monitoring according to claim 6 is characterized by: The calculation formula of the total phosphorus concentration ZL is as follows: ZL=[TPC×(TPD+TPG)-P2] / (L2×SQRT(W)); L2=(TPC-TPC0) / (ZL true -ZL0); TPD is the low range calibration value of the total phosphorus sensor; TPG is the high range calibration value of the total phosphorus sensor; P2 is the second offset, which reflects the offset degree of the zero point of the total phosphorus sensor; L2 is the second sensitivity coefficient and reflects the sensitivity of the total phosphorus sensor; TPC0 is the average output value of the total phosphorus sensor; ZL true is the actual total phosphorus concentration; ZL0 is the average concentration of total phosphorus.

8. The online water quality monitoring system for environmental monitoring according to claim 6 is characterized by: The online monitoring analysis based on the comprehensive water quality index SZ is as follows: If the water quality comprehensive index SZ shows an upward trend on the line graph, it means that the water quality is deteriorating, the system will receive an early warning message and immediately initiate the emergency response procedure; If the water quality comprehensive index SZ shows a downward trend on the line graph, it means that the water quality is improving and the system will maintain the current monitoring; If the comprehensive water quality index SZ shows a flat trend on the line graph, it means that the water quality is relatively stable and the system will increase the monitoring frequency.

9. The monitoring method of an online water quality monitoring system for environmental monitoring according to claim 1, characterized in that: The specific steps are as follows: Step 1: Use the data acquisition module to collect online monitoring data related to dissolved oxygen, chemical oxygen demand and total phosphorus of water quality in real time and convert them into digital signals; Step 2: Use the data transmission module to transmit the collected online monitoring data to the remote data center of the data processing module in real time; Step 3: Using the data processing module, calculate and output the dissolved oxygen concentration RY, the estimated value of chemical oxygen demand HY, and the comprehensive water quality index SZ in sequence; Step 4: Based on the comprehensive water quality index SZ, use the display and analysis module to display the water quality change trend and trend analysis; Step 5: Use the early warning and response module to provide timely early warning and control measures for changing trends.

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