CN-121978298-A - Water quality on-line monitoring system and method based on spectral electrode method and big data analysis

CN121978298ACN 121978298 ACN121978298 ACN 121978298ACN-121978298-A

Abstract

The invention relates to the technical field of environmental monitoring, and particularly discloses a water quality on-line monitoring system and method based on a spectrum electrode method and big data analysis, wherein the system comprises a water sampling unit, a water sampling unit and a water sampling unit, wherein the water sampling unit is used for extracting a water sample from a water body to be detected and conveying the water sample to a detection water tank; the monitoring instrument unit comprises a physical sensor group and a big data analysis module, wherein the physical sensor group adopts a sensor based on a spectrum method or electrode method principle and is used for directly measuring a plurality of basic physical and chemical parameters of a water sample, and the big data analysis module is in communication connection with the physical sensor group and is internally provided with a trained AI big data analysis model. The system and the method for on-line monitoring of water quality based on the spectral electrode method and the big data analysis achieve the purpose that no chemical reagent is needed in the core monitoring process, and the high cost and secondary pollution risks caused by reagent purchasing, storing and waste liquid treatment are thoroughly eliminated.

Inventors

WANG SHUHANG
ZHANG BO

Assignees

环建生态修复(北京)有限责任公司

Dates

Publication Date: 20260505
Application Date: 20260313

Claims (9)

1. A water quality on-line monitoring system based on a spectrum electrode method and big data analysis is characterized by comprising the following steps: The water sampling unit is used for extracting a water sample from the water body to be detected and conveying the water sample to the detection water tank; The monitoring instrument unit comprises a physical sensor group and a big data analysis module, wherein the physical sensor group adopts a sensor based on a spectrum method or an electrode method principle and is used for directly measuring a plurality of basic physical and chemical parameters of a water sample, the big data analysis module is in communication connection with the physical sensor group and is internally provided with a trained AI big data analysis model, and the model takes at least two basic parameters measured by the physical sensor group as input characteristics and carries out calculation and analysis through a preset algorithm model to indirectly calculate the total nitrogen concentration value and the total phosphorus concentration value in the water sample; The system control unit is electrically connected with the water collection unit and the monitoring instrument unit and is used for controlling the automatic operation, data acquisition and processing and remote communication of the system; The power supply unit is used for providing power for each unit of the system; The auxiliary unit comprises a cabinet, a lightning protection module, a heat preservation device and a heat dissipation device.
2. The system for on-line monitoring of water quality based on spectroscopic electrode method and big data analysis of claim 1 wherein said physical sensor group comprises sensors for measuring at least two of water temperature, conductivity, pH, dissolved oxygen, turbidity, ammonia nitrogen and permanganate index.
3. The online water quality monitoring system based on the spectral electrode method and the big data analysis of claim 1, wherein the AI big data analysis model is obtained through training a data set comprising historical physical sensor data and total nitrogen and total phosphorus true values corresponding to the national standard method.
4. The online water quality monitoring system based on the spectroelectrode method and the big data analysis according to claim 3, wherein the AI big data analysis model is constructed by the following steps: collecting a historical data set containing various basic parameters measured by the same principle equipment as the physical sensor group and accurate total nitrogen and total phosphorus values measured by a national standard chemical method of a corresponding water sample; Training the historical data set by using a machine learning algorithm, and establishing a prediction model from multidimensional basic parameters to total nitrogen and total phosphorus concentrations.
5. The system for on-line monitoring of water quality based on spectro-electrode method and big data analysis according to claim 1, wherein the system control unit comprises a flow control module configured to perform a periodic monitoring flow including the steps of draining, rinsing, water inflow, precipitation, and data acquisition.
6. The system for on-line monitoring of water quality based on spectral electrode method and big data analysis according to claim 5, wherein the system control unit further comprises: The intelligent controller is provided with a touch screen man-machine interface; The data management module is used for storing the original measurement data and the calculated total nitrogen/total phosphorus data; and the communication module supports a wireless network and is used for remotely uploading the monitoring data.
7. A method for on-line monitoring of water quality based on the system of any one of claims 1-4, comprising the steps of: S1, initializing a system; s2, executing an automatic monitoring process to finish the replacement and preparation of the water sample; S3, synchronously collecting a plurality of basic parameters of a water sample through a physical sensor group; s4, inputting the multiple basic parameters acquired in the S3 into a preset AI big data analysis model, and calculating and outputting the total nitrogen concentration value and the total phosphorus concentration value of the current water sample; S5, integrating and uploading basic parameter data and total nitrogen and total phosphorus data obtained through calculation; And S6, returning to a waiting state until the next acquisition period starts, and jumping to S2.
8. The method of on-line monitoring of water quality as set forth in claim 7, wherein the automated monitoring process in step S2 comprises draining, rinsing, water intake and precipitation operations.
9. The method of on-line monitoring of water quality as set forth in claim 7, wherein the basic parameters collected in step S3 include at least two of water temperature, conductivity, pH, dissolved oxygen, turbidity, ammonia nitrogen and COD.

Description

Water quality on-line monitoring system and method based on spectral electrode method and big data analysis Technical Field The invention relates to the technical field of environmental monitoring, in particular to a water quality on-line monitoring system and method based on a spectrum electrode method and big data analysis. Background The traditional water quality on-line monitoring method particularly adopts a chemical reagent method aiming at monitoring key indexes such as Chemical Oxygen Demand (COD), ammonia nitrogen, total phosphorus and the like. Although the methods have higher precision, the method has obvious defects of 1) high construction and operation cost, high total life cycle cost caused by the need of periodically supplementing and replacing expensive chemical reagents and processing waste liquid, 2) low monitoring frequency, high-frequency and real-time monitoring of chemical reactions which are difficult to realize in a few hours, 3) secondary pollution risk, and 4) complex system and frequent maintenance, wherein the complex flow paths, the reaction units and the reagent storage units are involved, the failure rate is high, and the maintenance workload is large. In recent years, physical detection technologies represented by a spectrometry method and an electrode method are attracting attention because of the advantages of reagent free, quick response, no secondary pollution and the like. However, when a physical sensor is simply used for directly measuring certain complex water quality indexes (such as total nitrogen and total phosphorus), the problems of weak anti-interference capability, insufficient measurement precision, poor correlation with a national standard method and the like often exist, and the application of the method in the serious environment supervision field is limited. Therefore, a new online water quality monitoring scheme which can combine the advantages of physical detection rapidity, economy and chemical method accuracy is urgently needed. Disclosure of Invention In order to solve the technical problems, the invention is realized by the following technical scheme that the water quality on-line monitoring system and method based on a spectrum electrode method and big data analysis comprise the following steps: The water sampling unit is used for extracting a water sample from the water body to be detected and conveying the water sample to the detection water tank; The monitoring instrument unit comprises a physical sensor group and a big data analysis module, wherein the physical sensor group adopts a sensor based on a spectrum method or an electrode method principle and is used for directly measuring a plurality of basic physical and chemical parameters of a water sample, the big data analysis module is in communication connection with the physical sensor group and is internally provided with a trained AI big data analysis model, and the model takes at least two basic parameters measured by the physical sensor group as input characteristics and carries out calculation and analysis through a preset algorithm model to indirectly calculate the total nitrogen concentration value and the total phosphorus concentration value in the water sample; The system control unit is electrically connected with the water collection unit and the monitoring instrument unit and is used for controlling the automatic operation, data acquisition and processing and remote communication of the system; The power supply unit is used for providing power for each unit of the system; The auxiliary unit comprises a cabinet, a lightning protection module, a heat preservation device and a heat dissipation device. Preferably, the physical sensor group includes sensors for measuring at least two of water temperature, conductivity, pH, dissolved oxygen, turbidity, ammonia nitrogen, and permanganate index (COD). Preferably, the AI big data analysis model is obtained through training a data set containing historical physical sensor data and total nitrogen and total phosphorus true values corresponding to a national standard method, and is constructed by the following steps: collecting a historical data set containing various basic parameters measured by the same principle equipment as the physical sensor group and accurate total nitrogen and total phosphorus values measured by a national standard chemical method of a corresponding water sample; Training the historical data set by using a machine learning algorithm, and establishing a prediction model from multidimensional basic parameters to total nitrogen and total phosphorus concentrations. Preferably, the system control unit includes: The intelligent controller is provided with a touch screen man-machine interface; the flow control module is configured to execute a periodic monitoring flow, and the flow at least comprises the steps of drainage, rinsing, water inlet, precipitation, data acquisition and storage; The data management module is used for