CN115656069A - Detection method of distributed water quality multi-parameter real-time model based on reflection spectroscopy - Google Patents
Detection method of distributed water quality multi-parameter real-time model based on reflection spectroscopy Download PDFInfo
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Abstract
The invention is suitable for the technical field of water quality monitoring, and provides a detection method of a distributed water quality multi-parameter real-time model based on a reflection spectroscopy, which comprises the following steps: surveying and collecting water samples on the spot; establishing a data set of a hyperspectral reflectance spectrum and water quality parameters of a water body; adopting a convolution neural network method to construct a water quality monitoring mathematical model; setting multi-point detection in the same water area, obtaining multi-point water quality parameters through multi-point spectral data, and calculating a water quality monitoring mathematical model according to the multi-point water quality parameters to obtain a water quality multi-parameter result of the water area; the automatic storage, real-time uploading, analysis and returning of water quality data are realized through big data analysis and AI analysis technologies; the front-end sensing equipment and the application system form an entity network for real-time communication through the technology of the Internet of things. The invention can analyze and evaluate the planar water quality condition of the water area through distributed water quality detection, and monitor a plurality of parameters of the water quality in real time.
Description
Technical Field
The invention belongs to the technical field of water quality monitoring, and particularly relates to a detection method of a distributed water quality multi-parameter real-time model based on a reflection spectroscopy.
Background
The conventional water quality and water environment monitoring and evaluation needs to arrange a large number of artificial monitoring points in a water area, and then accurate time-space distribution information of water quality or other water environment parameters can be obtained through laboratory analysis. The currently used water quality monitoring instruments have various interfaces and poor compatibility, are mostly connected by wires, have complex connecting lines and high cost, are difficult to realize in some large-scale detection fields, and greatly limit the development of water quality detection systems. Although quality of water automatic monitoring station can replace the manual work and can monitor in succession at the monitoring section, has saved a large amount of manpowers and time, and data volume is big and continuous moreover, but current quality of water automatic monitoring station is mostly with water contact probe, and these probe equipment are generally more expensive, and the monitoring index is single moreover. Water quality monitoring often requires multi-parameter monitoring, thus requiring a large number of probes and facilities for installing the equipment, and greatly increasing the construction cost. In addition, the probe is soaked in water for a long time, and periphyton and pollutant crystals are easy to grow on the probe, so that the sensitivity of the probe is reduced, and frequent cleaning and maintenance are required. This is a nuisance and makes the popularization of automatic water quality monitoring stations not very smooth.
In summary, the current informatization development is rapid, higher requirements are put forward on water environment monitoring, and the following technologies need to be solved: 1. a distributed hyperspectral reflectance spectrum water quality multi-parameter data model; 2. and (5) carrying out online detection research on the real-time model.
Disclosure of Invention
The invention aims to provide a detection method of a distributed water quality multi-parameter real-time model based on reflection spectroscopy, and aims to solve the problem of low detection accuracy of a distributed water quality multi-parameter real-time model
。
In order to achieve the purpose, the invention provides the following technical scheme:
the detection method of the distributed water quality multi-parameter real-time model based on the reflection spectroscopy comprises the following steps:
s11, investigating and collecting a water sample on the spot, and determining, detecting and evaluating water quality physicochemical parameters;
s12, acquiring water body spectrum data through a foundation survey station, establishing a data set of a water body hyperspectral reflectance spectrum and water quality parameters, and analyzing the correlation between various water quality parameters and reflectance spectra of different water bodies;
s13, constructing a water quality monitoring mathematical model by adopting a convolutional neural network method, performing model calculation, inspection and correction, and realizing real-time uploading and analysis of water quality analysis data by combining a foundation survey station;
s14, setting multi-point detection in the same water area, obtaining multi-point water quality parameters through multi-point spectral data, and calculating by using a water quality monitoring mathematical model according to the multi-point water quality parameters to obtain a water quality multi-parameter result of the water area;
s15, realizing automatic storage, real-time uploading, analysis and returning of water quality data through big data analysis and AI analysis technologies;
and S16, enabling the front-end sensing equipment and the application system to form a real-time communication entity network through the Internet of things technology.
Furthermore, in the step of investigating and collecting water samples on the spot, and measuring, detecting and evaluating the water quality physicochemical parameters, water samples 0.2m below the water surface, 0.5m in the middle layer and from the lake bottom are collected.
Further, the water quality physicochemical parameters comprise pollutant total nitrogen, ammonia nitrogen, nitrate nitrogen, nitrite nitrogen, total phosphorus and chemical oxygen demand.
Further, the concrete operations of the step of acquiring water body spectrum data through the foundation survey station and establishing a data set of the water body hyperspectral reflectance spectrum and the water quality parameters are as follows:
the method comprises the steps of acquiring water body spectrum data by using a foundation survey station, performing remote sensing inversion research on water quality parameters by using a GIS technology, an Internet of things technology and a big data technology, combining field actual measurement water body spectrum data and water quality parameter data by using environmental parameters, position parameters, space-time parameters and water body parameters, and establishing a data set of water body hyperspectral reflectance spectra and water quality physicochemical parameters.
Furthermore, the application system comprises a data acquisition module, a transmission communication module, a data analysis processing module and a power supply module, wherein the transmission communication module is used for automatically selecting a communication mode to transmit data according to the field communication condition, the data analysis processing module is used for automatically processing and analyzing data, and the power supply module is used for supplying power to the system.
Furthermore, the data acquisition module consists of a receiver and an antenna.
Further, the communication mode is one of 4G, 5G and Beidou short messages.
Compared with the prior art, the invention has the beneficial effects that:
according to the detection method of the distributed water quality multi-parameter real-time model based on the reflection spectroscopy, the planar water quality condition of a water area can be analyzed and evaluated through distributed water quality detection; by constructing the water quality monitoring mathematical model of the convolutional neural network method, the problems of poor environmental applicability and low precision of the traditional spectral analysis water quality monitoring algorithm are solved, the monitoring precision of the remote sensing inversion model and the adaptability of water monitoring are improved, and the flexibility, safety, intelligence and precision of water quality monitoring are improved; the system can monitor a plurality of water quality parameters in real time, and can ensure that water quality data can be automatically stored, uploaded in real time, analyzed, transmitted back and the like.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention is further described in detail with reference to the following embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.
Specific implementations of the present invention are described in detail below with reference to specific embodiments.
The detection method of the distributed water quality multi-parameter real-time model based on the reflection spectroscopy provided by the embodiment of the invention comprises the following steps:
s11, investigating and collecting a water sample on the spot, and determining, detecting and evaluating water quality physicochemical parameters;
s12, acquiring water body spectrum data through a foundation survey station, establishing a data set of water body hyperspectral reflectance spectrums and water quality parameters, and analyzing the correlation between various water quality parameters and reflectance spectrums of different water bodies;
s13, constructing a water quality monitoring mathematical model by adopting a convolutional neural network method, performing model calculation, inspection and correction, and realizing real-time uploading and analysis of water quality analysis data by combining a foundation survey station;
s14, setting multi-point detection in the same water area, obtaining multi-point water quality parameters through multi-point spectral data, and calculating a water quality monitoring mathematical model according to the multi-point water quality parameters to obtain a water quality multi-parameter result of the water area;
s15, realizing automatic storage, real-time uploading, analysis and returning of water quality data through big data analysis and AI analysis technologies;
and S16, enabling the front-end sensing equipment and the application system to form a real-time communication entity network through the Internet of things technology.
In the embodiment of the invention, preferably, a typical urban lake is investigated on the spot, water samples of different points and water surface layers (0.2 m below the water surface), middle layers and bottom layers (0.5 m away from the lake bottom) are collected, data are processed, and basic water quality physicochemical parameters such as total nitrogen, ammonia nitrogen, nitrate nitrogen, nitrite nitrogen, total phosphorus, chemical Oxygen Demand (COD) and the like which are main pollutants of the current river are measured, checked and evaluated. A water quality monitoring mathematical model is constructed by adopting a convolutional neural network method, the influence of factors such as turbidity, chromaticity, temperature and PH value is comprehensively considered, the problems of poor environmental applicability and low precision of the traditional spectral analysis water quality monitoring algorithm are solved, the monitoring precision of a remote sensing inversion model and the adaptability of water body monitoring are improved, and the flexibility, safety, intelligence and precision of water quality monitoring are improved. By means of the distributed water quality detection mode, the planar water quality condition of the water area can be analyzed and evaluated.
In the step of investigating and collecting water samples, measuring, detecting and evaluating physicochemical parameters of water quality, the water samples are collected at a depth of 0.2m below the water surface, at the middle layer and at a depth of 0.5m from the lake bottom.
As a preferred embodiment of the invention, the water quality physicochemical parameters comprise pollutant total nitrogen, ammonia nitrogen, nitrate nitrogen, nitrite nitrogen, total phosphorus and chemical oxygen demand.
In the embodiment of the invention, preferably, a typical urban lake is investigated on the spot, and basic water quality physicochemical parameters such as total nitrogen, ammonia nitrogen, nitrate nitrogen, nitrite nitrogen, total phosphorus, chemical Oxygen Demand (COD) and the like, which are main pollutants of the current river, are measured, checked and evaluated.
As a preferred embodiment of the present invention, the step of acquiring water body spectrum data by a foundation survey station and establishing a data set of a water body hyperspectral reflectance spectrum and a water quality parameter specifically comprises:
the method comprises the steps of acquiring water body spectrum data by using a foundation survey station, performing remote sensing inversion research on water quality parameters by using a GIS technology, an Internet of things technology and a big data technology, combining field actual measurement water body spectrum data and water quality parameter data by using environmental parameters, position parameters, space-time parameters and water body parameters, and establishing a data set of water body hyperspectral reflectance spectra and water quality physicochemical parameters.
As a preferred embodiment of the present invention, the application system includes a data acquisition module, a transmission communication module, a data analysis processing module, and a power supply module, wherein the transmission communication module is configured to automatically select a communication mode for data transmission according to a field communication condition, the data analysis processing module is configured to automatically process and analyze data, and the power supply module is configured to provide power supply for the system.
In the embodiment of the present invention, preferably, the power supply module provides a stable power supply for the system through a large-capacity battery.
As a preferred embodiment of the present invention, the data acquisition module is composed of a receiver and an antenna.
In the embodiment of the invention, preferably, the data acquisition module can ensure the monitoring precision and reliability.
As a preferred embodiment of the present invention, the communication mode is one of 4G, 5G and beidou short messages.
In the embodiment of the invention, preferably, the front-end sensing equipment and the application system form a real-time communication entity network through the internet of things technology, so that the real-time communication technology of 4G, 5G, beidou or higher communication protocols is realized, the real-time communication among the equipment is ensured, and the automatic storage, real-time uploading, analysis, returning and the like of the water quality data are ensured.
Example 1
(1) Content of the main study
The real-time water quality monitoring method comprises the steps of investigating the real places of Po Yang lake and typical urban lakes in Nanchang city, analyzing and testing water sample data by a multispectral reflectance spectrum method, establishing key water quality index data sets of multispectral reflectance spectrum, total nitrogen, total phosphorus, COD (chemical oxygen demand), ammonia nitrogen and the like of water, researching the correlation between various water quality parameters and the reflectance spectrum of different water bodies, constructing a water quality monitoring mathematical model of a convolutional neural network method, combining an intelligent modular water quality comprehensive measuring station to realize real-time uploading and analysis of water quality analysis data, and improving the flexibility, safety, intelligence and precision of water quality monitoring. The intelligent integrated communication terminal is developed in an integrated mode, and monitored and analyzed data are uploaded to the intelligent modularized comprehensive testing station through public-private integration and wide-narrow integration mobile communication.
1) Based on key parameters and a data set of multispectral reflectance spectrums, a water quality parameter monitoring model is constructed by adopting a convolution neural network method, and the model is optimized and perfected by combining water body and water quality parameters acquired at different positions and time;
2) The water quality module design of the intelligent modular water quality comprehensive measuring station is perfected through the research of a multi-model fusion algorithm of open multi-source water quality parameters;
3) A trusted computing system of the observation station is researched, and a computing and communication platform for trusted computing and flexible networking is provided.
(2) Research method
1) Data collection, sampling and detection
Comprehensively collect the data of the underlying surface, vegetation coverage, water body biology and the like of the area, search and collect Chinese and English literature data relevant to the research, fully understand the research dynamics and development trend of the relevant fields and make basic preparation for the development of the research.
Collecting water body samples at different positions and different times, processing the samples, and storing the samples as a training data set and a verification data set.
A. Basic data collection
Hydrology, climate, geology and landform data of the water body. Such as water level, water depth, water quantity, flow rate and flow direction changes;
water body coastal city distribution, industrial layout, pollution sources and pollution discharge conditions thereof, urban water supply and drainage conditions and the like;
the water body along the shore water resource status and the application. Such as drinking water source distribution, key water source protection areas, water body basin land functions, recent use plans and the like;
water quality monitoring data, hydrological actual measurement data, water environment research results and the like all the year round.
B. Distribution and number of sampling points
C. Principle of sampling
On the basis of comprehensively analyzing the investigation research result and related data, the monitoring section is representative in layout, and the spatial distribution and change rule of water quality and pollutants can be truly and comprehensively reflected; determining a monitoring section and a sampling point according to a monitoring purpose and a monitoring project and by considering factors such as manpower, material resources and the like;
a large amount of wastewater is discharged into the upstream and downstream of main residential areas and industrial areas of rivers; the upper stream of the merging port of the larger branch flow and the part where the merged branch flow is fully mixed with the main flow enter the river mouth of the sea river; river reach and areas of severe water and soil loss affected by tides; major entrances and exits of lakes, reservoirs, estuaries; the entrance and exit of international river exit and entrance border;
functional areas such as a drinking water source area, a water area with concentrated water resources, a main landscape visiting area, an aquatic entertainment area, a place where a major water conservancy facility is located and the like;
the cross section position should avoid the dead water area and the backwater area, and the river reach is selected as straight as possible, the riverbed is stable, the water flow is stable, and no torrent shoal is provided;
the measuring section of the hydrographic instrument is superposed with the hydrographic measuring section as much as possible; and requires convenient traffic and has obvious shore marks.
The number of spectral measurement of each target water body is more than 10, and the measurement time of each time at least covers one wave period so as to avoid measurement errors caused by the shaking of the ship. The average value of them was taken as the spectral curve of the sampling point.
And in order to facilitate indoor data analysis, real scenes of sampling points are photographed and recorded.
D. Sampling numbering rules
2) Model building and training
The method is used for measuring the basic water quality physicochemical parameters of major pollutants such as total nitrogen, ammonia nitrogen, nitrate nitrogen, nitrite nitrogen, total phosphorus, chemical Oxygen Demand (COD) and the like in the Po yang lake and rivers in the Jiangxi area at present. The method is characterized in that the spectral information of a large number of different water bodies collected and processed in the early stage is comprehensively considered, the influence of factors such as turbidity, chromaticity, temperature and PH value is comprehensively considered, and the water bodies are measured, inspected and evaluated by utilizing convolutional neural network modeling.
3) Model integration
And integrating the mathematical model into an intelligent modularized comprehensive survey station. The intelligent integrated communication terminal uploads the monitored and analyzed data to the intelligent modularized comprehensive survey station through public-private integration and wide-narrow integration mobile communication.
Results of the study
1) Description of spectral water quality monitoring data field
| Field(s) | Name (R) | Description of the invention | Remarks for note |
| deviceId | Collection device id | Device's own identification code | |
| longitude | Longitude (G) | Precision reserved 6 decimal | |
| latitude | Latitude | Precision retention of 6 decimal places | |
| date | Date of collection | YYYYMMDD, for example: 20200331 | |
| time | Time of acquisition | HHMMSS, e.g.: 091154 | |
| position | Acquisition position | ||
| no | Collection number | ||
| weather | Weather conditions | Cloudy, clear and evening | |
| skyRadiation | Sky radiation | ||
| waterRadiation | Radiation of water body | ||
| airTemperature | Air temperature | Unit. Degree.C | |
| windSpeed | Wind speed | Unit m/s | |
| windDirection | Wind direction | ||
| waterTemperature | Water temperature | Unit. Deg.C | Precision preserving 2-bit decimal |
| waterDepth | Depth of water | Unit m | Precision preserving 2-bit decimal |
| conductivity | Electrical conductivity of | Unit S/m | Precision preserving 2-bit fractional numbers |
| dissolvedOxygen | Dissolved oxygen | Unit mg/L | Precision preserving 2-bit decimal |
| turbidity | Turbidity of water | FTU/NTU | Precision preserving 2-bit decimal |
| ph | PH | Precision preserving 2-bit fractional numbers | |
| waterTransparency | Transparency of water body | Precision preserving 2-bit decimal | |
| phosphorus | Total phosphorus | TP Unit mg/L | Precision preserving 2-bit fractional numbers |
| nitrogen | Total nitrogen | TN units mg/L | Precision preserving 2-bit decimal |
| Chlorophyll a | Chlorophyll-a | Unit mg/L | Precision preserving 2-bit fractional numbers |
| codChromium | COD chromium | Unit mg/L | Precision preserving 2-bit fractional numbers |
| codManganese | COD manganese | Unit mg/L | Precision preserving 2-bit fractional numbers |
| ammoniaNitrogen | Ammonia nitrogen | Unit mg/L | Precision preserving 2-bit decimal |
| nitrateNitrogen | Nitrate nitrogen | Unit mg/L | Precision preserving 2-bit decimal |
| Suspended Solids | Suspended substance | Unit mg/L | Precision preserving 2-bit decimal |
| wavelength | Wavelength of light | nm | Precision preserving 2-bit decimal |
| centerPositionX | Central position X | Precision preserving 2-bit decimal | |
| centerPositionY | Center position Y | Precision preserving 2-bit decimal | |
| channelLength | Length of channel | Unit filament 1 filament =0.01 mm | Precision preserving 2-bit fractional numbers |
| channelWidth | Width of channel | Unit filament 1 filament =0.01 mm | Precision preserving 2-bit decimal |
| meanValue | Mean value | Precision preserving 2-bit decimal | |
| midValue | Median value of | Precision preserving 2-bit fractional numbers | |
| coordinate | Coordinate system | 01: beijing 54 coordinate system (BJZ 54) \8194; 02: new beijing 54 coordinate system 03: the west 80 coordinate system (XIAN 80) 04: WGS84 coordinate system (WGS 84) 05:2000 national geodetic coordinate system (CGCS 2000) 06: mars coordinate system 07: GCJ02 coordinate system (GCJ 02) 08: BD09 hectometre projection coordinate system |
The above is only a preferred embodiment of the present invention, and it should be noted that, for those skilled in the art, it is possible to make several variations and modifications without departing from the concept of the present invention, and these should be considered as the protection scope of the present invention, which will not affect the effect of the implementation of the present invention and the practicability of the patent.
Claims (7)
1. The detection method of the distributed water quality multi-parameter real-time model based on the reflection spectroscopy is characterized by comprising the following steps of:
s11, investigating and collecting a water sample on the spot, and determining, detecting and evaluating water quality physicochemical parameters;
s12, acquiring water body spectrum data through a foundation survey station, establishing a data set of a water body hyperspectral reflectance spectrum and water quality parameters, and analyzing the correlation between various water quality parameters and reflectance spectra of different water bodies;
s13, constructing a water quality monitoring mathematical model by adopting a convolutional neural network method, performing model calculation, inspection and correction, and realizing real-time uploading and analysis of water quality analysis data by combining a foundation test station;
s14, setting multi-point detection in the same water area, obtaining multi-point water quality parameters through multi-point spectral data, and calculating a water quality monitoring mathematical model according to the multi-point water quality parameters to obtain a water quality multi-parameter result of the water area;
s15, realizing automatic storage, real-time uploading, analysis and returning of water quality data through big data analysis and AI analysis technologies;
and S16, enabling the front-end sensing equipment and the application system to form a real-time communication entity network through the Internet of things technology.
2. The method as claimed in claim 1, wherein in the step of investigating and collecting water samples in the field, measuring, detecting and evaluating physicochemical parameters of water quality, the water samples are collected at a distance of 0.2m below the water surface, at a distance of 0.5m from the lake bottom, and at the middle layer.
3. The method of claim 2, wherein the water quality physicochemical parameters include total nitrogen, ammonia nitrogen, nitrate nitrogen, nitrite nitrogen, total phosphorus and chemical oxygen demand of pollutants.
4. The detection method of the distributed water quality multi-parameter real-time model based on the reflection spectroscopy as claimed in claim 1, wherein the step of acquiring the water body spectrum data through the foundation survey station and establishing the data set of the water body hyperspectral reflection spectrum and the water quality parameters comprises the following specific operations:
the method comprises the steps of acquiring water body spectrum data by using a foundation survey station, performing remote sensing inversion research on water quality parameters by using a GIS technology, an Internet of things technology and a big data technology, combining field actual measurement water body spectrum data and water quality parameter data by using environmental parameters, position parameters, space-time parameters and water body parameters, and establishing a data set of water body hyperspectral reflectance spectra and water quality physicochemical parameters.
5. The method as claimed in claim 1, wherein the application system comprises a data acquisition module, a transmission communication module, a data analysis processing module and a power supply module, the transmission communication module is used for automatically selecting a communication mode according to the field communication condition to transmit data, the data analysis processing module is used for automatically processing and analyzing data, and the power supply module is used for supplying power to the system.
6. The method for detecting the distributed water quality multi-parameter real-time model based on the reflection spectroscopy as claimed in claim 5, wherein the data acquisition module is composed of a receiver and an antenna.
7. The method for detecting the distributed water quality multi-parameter real-time model based on the reflection spectroscopy as claimed in claim 5, wherein the communication mode is one of 4G, 5G and Beidou short messages.
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