Water quality online real-time monitoring system based on big data
The big data-based online real-time water quality monitoring system solves the problems of systematic planning and data processing limitations in water quality monitoring systems, realizes efficient correlation processing and accurate early warning of water quality data, and improves the real-time performance and response speed of water quality monitoring.
Patent Information
- Application Number
- CN202511539235.2
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-10-27
- Publication Date
- 2026-01-06
- Estimated Expiration
- Not applicable · inactive patent
AI Technical Summary
The existing water quality monitoring system lacks systematic planning, cannot achieve differentiated monitoring, and has limited data processing mechanisms, resulting in insufficient monitoring efficiency, low early warning response, and difficulty in quickly identifying complex pollution events and accurately locating pollution sources.
The big data-based online real-time water quality monitoring system collects and processes water quality data in real time and generates early warning signals by setting up unit areas, constructing water quality monitoring models, and adopting a correlation water quality data processing mechanism.
It enables efficient correlation processing and accurate early warning of water quality data, improves the real-time performance and response speed of water quality monitoring, and can quickly identify complex pollution events and locate pollution sources.
Smart Images
Figure CN121276012A_ABST
Abstract
Description
TECHNICAL FIELD
[0001] The present application relates to the technical field of water quality monitoring, and particularly relates to a water quality online real-time monitoring system based on big data. BACKGROUND
[0002] In the field of water resource protection and water environment governance, water quality monitoring is a key means to master water quality status and prevent and control pollution risks. Traditional water quality monitoring relies on manual sampling and laboratory analysis, and has problems such as low monitoring frequency, strong data lag, limited coverage, and the like, and is difficult to meet the rapid response demand of sudden pollution events. For example, when industrial wastewater is secretly discharged, agricultural non-point source pollution spreads, and the like, manual monitoring often needs several hours to several days to obtain data, resulting in delayed pollution control opportunity and expanded ecological damage.
[0003] With the development of Internet of Things and sensor technology, online monitoring equipment is gradually applied to water quality monitoring scenes, but the existing system still has significant technical bottlenecks. On the one hand, the sensor layout lacks systematic planning, and a single regional uniform distribution mode is mostly used, and different pollution risk areas cannot be monitored differently, resulting in data redundancy in core areas and data loss in edge areas. On the other hand, the data of each monitoring point is in an isolated state, and the internal correlation between parameters cannot be established, for example, the cooperative change rule of conventional parameters (such as pH value, dissolved oxygen) and pollutant parameters (such as COD, heavy metal) is not effectively mined, and it is difficult to identify a complex pollution event.
[0004] In addition, the limitation of the data processing mechanism further restricts the monitoring efficiency. The traditional system mostly uses a single threshold to judge the abnormality, and ignores the time-space dynamic characteristics of water quality parameters - the normal fluctuation range of the same parameter in different seasons and different regions is significantly different, and a fixed threshold is easy to cause false alarm or missed alarm. At the same time, pollution diffusion has significant spatial conductivity, and the existing system lacks linkage analysis of data between regions, and cannot realize gradient early warning from the periphery to the core area, and it is difficult to accurately locate the pollution source and diffusion path.
[0005] In the aspect of early warning response, the existing system mostly triggers early warning for a single abnormal index, and does not form a multi-dimensional early warning system, and it is difficult for management personnel to quickly judge the pollution level and the influence range. For example, when the COD of a certain area exceeds the standard, the system cannot synchronously push key information such as upstream pollution source investigation suggestion and downstream diffusion risk prediction, resulting in low efficiency of emergency decision-making.
[0006] In order to solve the above technical problems, the present application provides a water quality online real-time monitoring system based on big data. SUMMARY
[0007] In order to solve the above technical problems, the present application provides a water quality online real-time monitoring system based on big data. The object of the application can be achieved by the following technical solutions: a water quality online real-time monitoring system based on big data, comprising a water quality data real-time acquisition subsystem and a water quality data real-time monitoring subsystem; the water quality data real-time monitoring subsystem comprises a water quality data processing module and a water quality data early warning module; The water quality data real-time acquisition subsystem is used to set a unit area and construct a water quality monitoring model according to the unit area; water quality data is acquired based on the water quality monitoring model, and a water quality data unit is formed; The water quality data processing module is used to set an associated water quality data processing mechanism, and the water quality data unit is processed based on the associated water quality data processing mechanism to obtain abnormal water quality data; The water quality data early warning module performs early warning processing on the abnormal water quality data.
[0008] Further, the process of setting a unit area by the water quality data real-time acquisition subsystem comprises: A target water quality monitoring area is acquired, a key water quality monitoring point is set in the target water quality monitoring area, a sensor maximum area radius is set, and a sensor maximum area corresponding to the sensor maximum area radius is acquired with the key monitoring point as the center; The sensor maximum area radius is evenly divided into three segments and marked as a unit data change radius; the sensor maximum area is evenly divided into three unit areas according to the unit data change radius, and marked as a first data change area, a second data change area and a third data change area.
[0009] Further, the process of constructing a water quality monitoring model according to a unit area comprises: A water quality parameter type corresponding to the sensor is acquired; parameter monitoring nodes of different water quality parameter types are set in the three unit areas, and the parameter monitoring nodes corresponding to the same unit area are combined to form a unit water quality monitoring unit; An associated chain corresponding to the unit water quality monitoring unit is set, and the unit water quality monitoring units corresponding to the first data change area, the second data change area and the third data change area are sequentially bidirectionally associated to generate a bidirectional water quality monitoring unit through the associated chain; The unit water quality monitoring units of the bidirectional water quality monitoring unit are set with corresponding acquisition frequencies according to the first data change area, the second data change area and the third data change area to construct a monitoring model.
[0010] Further, the process of acquiring water quality data based on the water quality monitoring model and forming a water quality data unit comprises: The water quality data acquired by the unit water quality monitoring unit through the corresponding acquisition frequencies is sequentially connected to generate an associated water quality data chain; The associated water quality data chain corresponding to the unit water quality monitoring unit is sequentially connected according to the first data change region, the second data change region and the third data change region to generate a water quality data unit.
[0011] Further, the process of setting the associated water quality data processing mechanism by the water quality data processing module includes: The associated water quality data processing mechanism includes a water quality parameter type association mechanism and a unit association mechanism. The water quality parameter type mechanism is used to set a historical collection time period, collect historical water quality data of each parameter monitoring node of different unit water quality monitoring units in the historical collection time period based on big data, integrate historical water quality data of the same water quality parameter type to obtain a corresponding historical average value, and further associate all water quality parameter types of the unit water quality monitoring unit through a correlation coefficient to generate a unit water quality parameter type association chain.
[0012] Further, a recent time period is set, the correlation coefficients of the unit water quality parameter type association chain are trained through the recent time period, the associated data is updated to obtain the latest correlation coefficients. The unit association mechanism is used to obtain water quality data differences of the same water quality parameter type of adjacent unit water quality monitoring units from the inside unit water quality monitoring unit, which are respectively marked as a first water quality data difference and a second water quality data difference, and obtain a water quality data difference gradient value between the first water quality data difference and the second water quality data difference. The water quality data difference gradient value threshold of the adjacent unit water quality monitoring unit is set according to the water quality parameter type, and compared with the corresponding water quality data difference gradient value. If the water quality data difference gradient value is greater than or equal to the water quality difference threshold, the collection frequency of the first unit water quality monitoring unit is transmitted to the second unit water quality monitoring unit and the third unit water quality monitoring unit through the association chain, and then the collection frequencies of the unit water quality monitoring units are kept consistent, marked as the latest collection frequency; the water quality data is collected according to the latest collection frequency, marked as the latest water quality data. On the contrary, no processing is done.
[0013] Further, the process of processing the water quality data unit based on the associated water quality data processing mechanism to obtain abnormal water quality data includes: The water quality parameter type mechanism based on the associated water quality data processing mechanism obtains the unit water quality parameter type association chain in real time according to the latest correlation coefficients. The correlation coefficient threshold of each correlation coefficient is set, and compared with the corresponding correlation coefficient respectively. If there is a correlation coefficient greater than or equal to the correlation coefficient threshold, the corresponding unit water quality parameter type association chain is marked as an abnormal unit water quality parameter type association chain. Conversely, no processing is done; The water quality data threshold range corresponding to the water quality parameter type is set, and compared with the latest water quality data; If there is no water quality data threshold range, the corresponding latest water quality data is marked as abnormal latest water quality data; Conversely, no processing is done.
[0014] Further, the process of the water quality data warning module for the abnormal water quality data warning processing includes: The abnormal unit water quality parameter type association chain and the abnormal latest water quality data are generated to form corresponding warning signals, which are marked as first warning signal and second warning signal respectively; The warning signal is sent to the preset management terminal for processing.
[0015] Compared with the prior art, the beneficial effects of the present application are: BRIEF DESCRIPTION OF DRAWINGS
[0016] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the drawings needed in the embodiments will be briefly introduced. Obviously, the drawings described below are only some embodiments of the present application, and other drawings can be obtained by those skilled in the art based on these drawings.
[0017] Figure 1 The schematic diagram of the present application. DETAILED DESCRIPTION
[0018] The technical solutions in the embodiments of the present application will be described clearly and completely below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only some embodiments of the present application, not all embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor fall within the scope of the present application.
[0019] As Figure 1 shown, a water quality online real-time monitoring system based on big data, the system includes a water quality data real-time acquisition subsystem and a water quality data real-time monitoring subsystem; the water quality data real-time monitoring subsystem includes a water quality data processing module and a water quality data warning module; The water quality data real-time acquisition subsystem is used for setting unit area of the water quality data real-time acquisition subsystem, and constructing a water quality monitoring model according to the unit area; water quality data is collected based on the water quality monitoring model, and water quality data units are formed; The water quality data processing module is configured to set an associated water quality data processing mechanism, and to process water quality data units based on the associated water quality data processing mechanism to obtain abnormal water quality data. The water quality data early warning module is configured to perform early warning processing on the abnormal water quality data.
[0020] It should be further noted that the water quality data real-time acquisition subsystem sets a unit area and constructs a water quality monitoring model according to the unit area, and the process includes: A target water quality monitoring area is obtained, a key water quality monitoring point is set in the target water quality monitoring area, a maximum sensor area corresponding to a maximum sensor radius is obtained with the key monitoring point as the center, and the maximum sensor radius is set. The maximum sensor radius is evenly divided into three segments, which are marked as unit data change radii; the maximum sensor area is evenly divided into three unit areas according to the unit data change radii, which are respectively marked as a first data change area, a second data change area, and a third data change area. In the above embodiment, it should be further noted that the first data change area, the second data change area, and the third data change area are all centered on the same key monitoring point; and the radii are one unit data change radius, two unit data change radii, and three unit data change radii, respectively; and the third data change area is the outermost. A water quality parameter type corresponding to the sensor is obtained, and the water quality parameter type includes a regular parameter, an organic pollutant parameter, and an inorganic pollutant parameter. It should be further noted that the regular parameter includes but is not limited to pH value, dissolved oxygen, turbidity, conductivity, temperature, oxidation-reduction potential, etc.; the organic pollutant parameter includes but is not limited to chemical oxygen demand, permanganate index, total organic carbon, etc.; and the inorganic pollutant parameter includes but is not limited to heavy metals, toxic organic matter, algal density / chlorophyll a, biological toxicity, etc. Parameter monitoring nodes of different water quality parameter types are set in the three unit areas, and the parameter monitoring nodes corresponding to the same unit area are combined to form a unit water quality monitoring unit. An associated chain corresponding to the unit water quality monitoring unit is set, and the unit water quality monitoring units corresponding to the first data change area, the second data change area, and the third data change area are sequentially bidirectionally associated to generate bidirectional water quality monitoring units through the associated chain. Each unit water quality monitoring unit of the bidirectional water quality monitoring unit is set with a corresponding acquisition frequency according to the first data change area, the second data change area, and the third data change area to construct a monitoring model. The corresponding acquisition frequencies are respectively marked as 3a, 2a, and a; and a represents a unit acquisition frequency. In the above embodiments, it should be further explained that the unit water quality monitoring unit is marked as the first unit water quality monitoring unit, the second unit water quality monitoring unit, and the third unit water quality monitoring unit according to the first data change area, the second data change area, and the third data change area, respectively; the data monitored by the parameter monitoring node corresponding to the unit area closer to the key water quality monitoring point is larger; the parameter monitoring nodes of the same unit area are grouped into a unit water quality monitoring unit, the purpose of which is to ensure the time synchronization of data in key areas and provide data support for instantaneous source tracing of sudden pollution (such as poisoning); an association chain is set to bidirectionally associate the unit water quality monitoring units to generate a bidirectional water quality monitoring unit, wherein the bidirectional association chain has a transmission function and can transmit time, frequency, water quality monitoring data, etc.
[0021] It should be further explained that the process of collecting water quality data based on the water quality monitoring model and forming water quality data units includes: The water quality data collected by each parameter monitoring node of the unit water quality monitoring is sequentially connected through the corresponding acquisition frequency to generate an associated water quality data chain. The associated water quality data chain corresponding to the unit water quality monitoring unit is sequentially connected according to the first data change area, the second data change area, and the third data change area to generate a water quality data unit.
[0022] It should be further explained that the process of setting up the associated water quality data processing mechanism in the water quality data processing module includes: The associated water quality data processing mechanism includes a water quality parameter type association mechanism and a unit association mechanism; The water quality parameter type mechanism is used to set the historical collection time period, collect historical water quality data of each parameter monitoring node of different water quality monitoring units based on big data, and integrate historical water quality data of the same water quality parameter type to obtain the corresponding historical average; then, all water quality parameter types of a unit water quality monitoring unit are correlated with each other through correlation coefficients to generate a unit water quality parameter type association chain. Set a recent time period, train the correlation coefficient of the unit water quality parameter type association chain through the recent time period, and update the association data to obtain the latest correlation coefficient; The unit association mechanism is used to obtain the water quality data difference of the same water quality parameter type between adjacent water quality monitoring units starting from the inner unit of the bidirectional water quality monitoring unit, and to mark them as the first water quality data difference and the second water quality data difference respectively; and to obtain the water quality data difference gradient value between the first water quality data difference and the second water quality data difference. In the above embodiments, it should be further explained that all water quality data are collected within one cycle by three unit water quality monitoring units at a collection frequency; the adjacent unit water quality monitoring units include a first unit water quality monitoring unit and a second unit water quality monitoring unit, as well as a second unit water quality monitoring unit and a third unit water quality monitoring unit; Set the threshold value for the gradient value of water quality data difference between adjacent water quality monitoring units according to the type of water quality parameters; and compare it with the corresponding gradient value of water quality data difference. If the gradient value of the water quality data difference is greater than or equal to the water quality difference threshold, the acquisition frequency of the first water quality monitoring unit is transmitted to the second and third water quality monitoring units through the association chain; then the acquisition frequency of the unit water quality monitoring units is kept consistent and marked as the latest acquisition frequency; water quality data is acquired according to the latest acquisition frequency and marked as the latest water quality data; Conversely, no action is taken.
[0023] In the above embodiments, it should be further explained that the water quality data difference gradient value can better determine the changes in water quality data; if the water quality data difference gradient value is greater than or equal to the water quality data difference gradient value, it indicates that there is a large amount of abnormal water quality data in the target water quality monitoring area.
[0024] It should be further explained that the process of processing water quality data units based on the correlation water quality data processing mechanism to obtain abnormal water quality data includes: The water quality parameter type mechanism based on the correlation water quality data processing mechanism obtains the unit water quality parameter type correlation chain in real time according to the latest correlation coefficient; Set the threshold values for each correlation coefficient and compare them with the corresponding correlation coefficients. If there is a correlation coefficient greater than or equal to the correlation coefficient threshold, the corresponding unit water quality parameter type correlation chain is marked as an abnormal unit water quality parameter type correlation chain. Conversely, no action is taken; Set the water quality data threshold range corresponding to the water quality parameter type and compare it with the latest water quality data; If no water quality data threshold range exists, the latest water quality data will be marked as abnormal latest water quality data. Conversely, no action is taken.
[0025] It should be further explained that the process of the water quality data early warning module in processing abnormal water quality data includes: The association chain of water quality parameter types of abnormal units and the latest abnormal water quality data are used to generate corresponding early warning signals, which are marked as the first early warning signal and the second early warning signal, respectively. The warning signal is sent to a pre-set management terminal for processing.
[0026] Working principle: This invention uses a real-time water quality data acquisition subsystem to set up a unit area and construct a water quality monitoring model based on the unit area; it collects water quality data based on the water quality monitoring model and forms water quality data units; it sets up a correlated water quality data processing mechanism to process the water quality data units and obtain abnormal water quality data; and then it performs early warning processing on abnormal water quality data; effectively improving the correlation of online water quality monitoring.
[0027] The features and exemplary embodiments of various aspects of this application will be described in detail above. In order to make the purpose, technical solution and advantages of this application clearer, the application will be further described in detail above with reference to the accompanying drawings and specific embodiments. It should be understood that the specific embodiments described herein are only intended to explain this application and not to limit this application. For those skilled in the art, this application can be implemented without some of the details in these specific details. The above description of the embodiments is only to provide a better understanding of this application by showing examples of this application.
[0028] The above embodiments are only used to illustrate the technical methods of the present invention and are not intended to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical methods of the present invention without departing from the spirit and scope of the technical methods of the present invention.
Claims
1. A big data based water quality online real-time monitoring system, characterized in that, The system comprises a water quality data real-time acquisition subsystem and a water quality data real-time monitoring subsystem; the water quality data real-time monitoring subsystem comprises a water quality data processing module and a water quality data early warning module; The water quality data real-time acquisition subsystem is configured to set a unit area and construct a water quality monitoring model according to the unit area; water quality data is acquired based on the water quality monitoring model, and a water quality data unit is formed; The water quality data processing module is configured to set an associated water quality data processing mechanism, and process the water quality data unit based on the associated water quality data processing mechanism to obtain abnormal water quality data; The water quality data early warning module is configured to perform early warning processing on the abnormal water quality data.
2. The online real-time water quality monitoring system based on big data according to claim 1, characterized in that, The process of setting a unit area by the water quality data real-time acquisition subsystem comprises: A target water quality monitoring area is acquired, a key water quality monitoring point is set in the target water quality monitoring area, a maximum sensor area radius is set, and a maximum sensor area corresponding to the maximum sensor area radius is acquired with the key monitoring point as the center; The maximum sensor area radius is evenly divided into three segments, which are marked as unit data change radii; the maximum sensor area is evenly divided into three unit areas according to the unit data change radii, which are marked as a first data change area, a second data change area, and a third data change area, respectively.
3. The online real-time water quality monitoring system based on big data according to claim 2, characterized in that, The process of constructing a water quality monitoring model according to a unit area comprises: A water quality parameter type corresponding to a sensor is acquired; parameter monitoring nodes of different water quality parameter types are set in the three unit areas, respectively; and the parameter monitoring nodes corresponding to the same unit area are combined to form a unit water quality monitoring unit; An associated chain corresponding to the unit water quality monitoring unit is set, and the unit water quality monitoring units corresponding to the first data change area, the second data change area, and the third data change area are sequentially associated in both directions through the associated chain to generate a bidirectional water quality monitoring unit; The unit water quality monitoring units of the bidirectional water quality monitoring unit are set with corresponding acquisition frequencies according to the first data change area, the second data change area, and the third data change area to construct a monitoring model.
4. The online real-time water quality monitoring system based on big data according to claim 3, characterized in that, The process of acquiring water quality data based on the water quality monitoring model and forming a water quality data unit comprises: The water quality data acquired by the parameter monitoring nodes of the unit water quality monitoring unit through the corresponding acquisition frequencies are sequentially connected to generate an associated water quality data chain; The associated water quality data chains corresponding to the unit water quality monitoring units are sequentially connected according to the first data change area, the second data change area, and the third data change area to generate a water quality data unit.
5. The online real-time water quality monitoring system based on big data according to claim 4, characterized in that, The process of setting an associated water quality data processing mechanism by the water quality data processing module comprises: The associated water quality data processing mechanism comprises a water quality parameter type association mechanism and a unit association mechanism; The water quality parameter type mechanism is configured to set a historical acquisition time period, acquire historical water quality data corresponding to each parameter monitoring node of different unit water quality monitoring units in the historical acquisition time period based on big data, integrate the historical water quality data of the same water quality parameter type to obtain a corresponding historical mean value, and then associate all water quality parameter types of the unit water quality monitoring unit with each other through an association coefficient to generate a unit water quality parameter type association chain.
6. The online real-time water quality monitoring system based on big data according to claim 5, characterized in that, A recent time period is set, and the correlation coefficients of the unit water quality parameter type association chain are trained through the recent time period, and the correlation data is updated to obtain the latest correlation coefficients; The unit correlation mechanism is used to obtain the water quality data difference value of the same water quality parameter type of the adjacent unit water quality monitoring unit from the inside unit water quality monitoring unit, which is marked as the first water quality data difference value and the second water quality data difference value; and the water quality data difference gradient value between the first water quality data difference value and the second water quality data difference value is obtained; The water quality data difference gradient value threshold of the adjacent unit water quality monitoring unit is set according to the water quality parameter type; and the corresponding water quality data difference gradient value is compared; If the water quality data difference gradient value is greater than or equal to the water quality difference threshold, the collection frequency of the first unit water quality monitoring unit is transmitted to the second unit water quality monitoring unit and the third unit water quality monitoring unit through the association chain; then the collection frequency of the unit water quality monitoring unit is kept consistent, which is marked as the latest collection frequency; The water quality data is collected according to the latest collection frequency, which is marked as the latest water quality data; On the contrary, no processing is done.
7. The online real-time water quality monitoring system based on big data according to claim 6, characterized in that, The process of processing the water quality data unit to obtain abnormal water quality data based on the associated water quality data processing mechanism includes: The unit water quality parameter type association chain is obtained in real time according to the latest correlation coefficient based on the water quality parameter type mechanism of the associated water quality data processing mechanism; The correlation coefficient threshold of each correlation coefficient is set, and the corresponding correlation coefficient is compared; If there is a correlation coefficient greater than or equal to the correlation coefficient threshold, the corresponding unit water quality parameter type association chain is marked as an abnormal unit water quality parameter type association chain; On the contrary, no processing is done; The water quality data threshold range corresponding to the water quality parameter type is set, and the latest water quality data is compared; If there is no water quality data threshold range, the corresponding latest water quality data is marked as abnormal latest water quality data; On the contrary, no processing is done.
8. The online real-time water quality monitoring system based on big data according to claim 7, characterized in that, The process of the water quality data warning module for pre-warning processing of abnormal water quality data includes: The abnormal unit water quality parameter type association chain and the abnormal latest water quality data generate corresponding warning signals, which are marked as the first warning signal and the second warning signal, respectively; The warning signal is sent to the preset management terminal for processing.